Gartner’s coining of the term last year has helped enterprises in need of IT orchestration and cloud adoption home in on their needs. Solutions that fall under this umbrella term can help orchestrate end-to-end processes and provide high-level views of enterprise infrastructures.

DPCs are relatively a new concept. To help you better understand the landscape, we will explore what DPCs entail, key features, and top solutions on the market today.

What are Digital Platform Conductor Tools?

Digital platform conductor tools are solutions that assist organizations with managing and organizing their infrastructure. Some of the most common struggles enterprise IT teams face are data silos and integration challenges. DPCs integrate your existing tools and systems with one another. This helps manage workloads, and more importantly, standardize your infrastructure across environments.

These solutions are closest in functionality to Service Orchestration and Automation Platforms (SOAP). They help enterprises accomplish the following:

• Workflow orchestration
• Event-driven automation
• Self-service automation
• Scheduling, monitoring, visibility, alerting
• Resource provisioning
• Managing data pipelines

Because many DPCs and SOAPs have interchangeable features, experts predict that enterprises will soon start to market all these solutions as DPCs only.

Key Features of Digital Platform Conductor Tools

The best DPC tools have the following features:

• Automated data collection
• Workload automation
• Cloud service automation
• Data cleanup
• Dependency mapping
• Big data pipeline orchestration
• Hybrid cloud file transfers

Top Digital Platform Conductor Tools

Stonebranch

A legacy player in the DPC space, Stonebranch offers more than 20 years of IT orchestration and automation experience for enterprises. The company offers a number of convenient integrations with Salesforce, Pentaho, Databricks, and Snowflake to help automate jobs and orchestrate operations. Enterprises can gain these integrations free of charge.

They’ve worked with clients like Expedia Group, PSCU, and Weis Markets to drive business automation and make processes more efficient. Furthermore, Stonebranch has been a major player in legitimizing DPCs on the market. The team authors blog posts educating enterprises on what they are and how they can be leveraged.

Key Features:

• Automate your workload in one hub. This helps you build, schedule, and manage all IT tasks centrally.
• Centralize automated jobs that help support end-to-end processes.
• Manage automation in private, public, and multi-cloud landscapes.
• Unite developers and IT teams through DevOps orchestration.
• Manage B2B file transfers with provided third-party vendors.
• Schedule enterprise jobs for backend work of the IT department.

Pros: 

• Task creation is capable and simple to carry out
• Customers report that the software is user-friendly
• Workflows are easy to create with drag-and-drop features

Cons:

• Adding temporary workflow edits can be laborious
• The solution comes with a steep learning curve
• Some customers would like a larger list of native integrations

ReadyWorks

ReadyWorks has been at the forefront of adopting DPCs and helping customers to leverage their benefits. Much like Stonebranch, they’ve published pieces educating the public and enterprises on the space.

Its differentiating factor for enterprise customers is its four-module method to conduct data, systems, and people. These four modules help enterprises integrate data, analyze and plan, conduct, and visualize data. The company’s cloud infrastructure models are very flexible, allowing enterprises to choose from public, multi, private, and hybrid solutions.

Key Features:

• Centralize data in real time from every IT system of record.
• Gain holistic pictures of your data by importing spreadsheets, text files, and other compiled data sources.
• Report creation assists with analyzing information, driving program decisions, and initiating workflows.
• Dependency mapping is highly flexible. This allows businesses to see which applications are in the data center and gain a picture of their infrastructure.
• Maintain history of your IT program and receipts through audit trails. Track purchases, deployment, task completion, and end user communication.

Pros: 

• Integration and deployment are simple to carry out
• Customers can automate communications and reporting
• ReadyWorks’ team is highly accessible and helpful

Cons:

• Some customers state that advanced reporting is still being built out
• The program comes with a steep learning curve
• Some tasks and screens are not as intuitive as alternatives

Cloudsoft

Cloudsoft not only helps enterprises with IT orchestration but with cloud cost optimization as well. In fact, it’s this personalized approach to data integration and analysis that sets Cloudsoft apart from other DPCs.

Enterprises can expect assistance from Cloudsoft through its six-pillar approach. These pillars cover operational excellence, performance, reliability, security, cost optimization, and sustainability. Customers should note that Cloudsoft tends to market its solution heavily towards the financial industry. This is because many financial institutions still rely on older business models. Although this niche is something the company has its eyes towards, its solutions are industry-agnostic.

Key Features:

• Effectively eliminate data silos by centralizing your estate.
• Intelligent, AI-driven automation reduces provisioning time and manages the lifecycle of applications. 
• Monitor legacy applications specifically. This allows businesses to take advantage of scalability and the quicker development cycle of the cloud.
• Onboarding team assists with database modernization, as well as operations and security improvements.
• Cloudsoft provides blueprints and policies to prove FCA and EU regulation compliance.

Pros: 

• The company offers a multitude of secondary resources for onboarding
• Workflows can be created through drag and drop
• The customer service team is very responsive

Cons:

• The program is heavily geared towards AWS, which could be limiting for some
• Microsoft Azure users will find better support with alternative tools
• In a similar vein, the program is targeted towards FinOps and financial institutions

Flexera

For over 34 years, Flexera has been an industry leader when it comes to IT orchestration and cloud migration. The organization prides itself on staying on top of industry news, such as the Log4j exploits.

The organization assists with IT asset management and visibility. Enterprises can connect with the team at Flexera for guidance in cloud cost optimization as well. One of the most helpful standout features Flexera offers is its high-level view of SaaS spend and utilization. With data democratization, enterprises are adopting a multitude of SaaS platforms and simply lose track. Flexera helps enterprises calculate the exact ROI they face in this new age.

Key Features:

• IT orchestration and insights help inform you of spend, risk, and overall IT ecosystem.
• Overview provides unique insights, such as the number of outdated versions and products.
• Flexible variety of infrastructures are supported. This includes on-premise, SaaS, and cloud.
• Self-healing capabilities are offered, including automated backup, auto-scaling arrays, and automated failover.

Pros: 

• The organization is particularly targeted towards enterprises
• Customers can expect high level security when adopting the tool
• The solution is highly customizable for different customer-types

Cons:

• Users report the software for being rather slow at times
• Onboarding is rather expensive, costing $14K for basic installations
• The program’s user interface is clunkier than alternatives

How to Choose DPC Tools

Selecting the right DPC tool boils down to three key factors:

1. Evaluate your needs

The foundational step to choosing the right DPC tool is evaluating what exactly your needs are.

The two driving factors behind most enterprises adopting DPC solutions are a need for IT orchestration and assistance in cloud adoption. If you’re a key enterprise leader, connect with your IT team and inquire about their needs as well. This will help you gain a greater understanding of where your business stands in regards to DPC adoption.

2. Learn the landscape

DPC solutions are very transparent about their target audiences and use cases. Be sure to inquire with sales teams and conduct research on enterprises in your industry and how they’ve benefited from DPC adoption.

Many of the solutions we outlined above, such as ReadyWorks and Stonbranch, produce helpful pieces of content regarding the market and how DPCs are used by various industries. These use cases can help you gain a greater understanding of the tangible benefits these solutions offer. They also help you gain greater context into your own needs as well.

3. Carve out budget

Once you have an understanding of your company’s needs and how leaders in your industry have leveraged various DPC solutions, it’s time to build a budget and connect with sales representatives.

Again, the concept of DPCs was just materialized this past year. Make sure to gain a clear picture of what each platform can bring to the table for your enterprise, and don’t hesitate to inquire about additional features and pricing packages. Many of these companies are rapidly growing and eager to assist.

Read next: Best Data Migration Tools and Software 2022

The post Top Digital Platform Conductor Tools appeared first on Enterprise Networking Planet.

Enterprise data management is an industry-agnostic issue. In response to this, we’ve conducted research and pulled from our expertise to compile the top data management systems on the market today as well as their individual benefits.

What is a Data Management Platform?

A data management platform is a tool used in different industry verticals to aggregate, store, and analyze data from a multitude of sources. Sources can be in-house or through third parties.

The growth of DMPs is a direct result of enterprises developing big data strategies in the 21st century. The sheer volume, velocity, and variety of data sets enterprises have grown accustomed to are made viable through DMPs.

The primary use cases for DMPs, no matter the industry, include:

• Segmenting and scaling audiences
• Analyzing audience and behavioral data
• Customer acquisition

Also read: Simplifying Data Management with Hybrid Networks 

What Are the Benefits of a Data Management Platform?

The best data management platforms provide enterprises with the following benefits:

• Consolidating large data sets in one platform
• Increasing overall revenue
• Integrating second  and third-party data to analyze new markets
• Building more targeted marketing campaigns
• Segmenting customers and audience sets
• Increasing content value

Best Data Management Platforms

Here are six leaders in the market to consider. We’ve provided key features, pros and cons, as well as pricing for a high-level overview of each vendor.

Adobe Audience Manager

Although Adobe is best known for its design software, its Audience Manager is a powerful business solution. Organizations such as Hyatt, Virgin Holidays, and Sky have all utilized Audience Manager to consolidate data, segment audiences, and analyze new insights.

This platform is just a piece of Adobe’s Experience Cloud package. The kit of software tools helps enterprises complete e-signatures, complete end-to-end user journeys, and scale AI-driven marketing campaigns. The fact that Audience Manager integrates seamlessly with these solutions is its differentiating factor for enterprises.

Key Features:

• A/B test segmentation
• Bi-directional, real-time data integration with Adobe Analytics
• First-party audience data transfer
• Algorithmic modeling for predictive audience analysis
• Organization ID

Pros: 

• It integrates seamlessly with Adobe Experience Cloud software
• Customers report that the software is user-friendly
• It is cloud-based and easy to access

Cons:

• Load times for data are rather long
• Customers commonly complain about pricing
• The solution comes with a steep learning curve

Pricing: Adobe does not share pricing plans for Audience Manager with the public. Businesses must contact Adobe directly for a quote based on their needs and company size.

Oracle BlueKai

When tech giant Oracle purchased BlueKai for an estimated $400 million in 2014, it instantly became a leader in the DMP market. Six years later, Oracle BlueKai is now an essential component of Oracle’s CX Marketing lineup of solutions. One of its driving factors for enterprises is its ability to engage ready-to-buy customers.

What’s most striking about Oracle BlueKai is the team’s approach to marketing and ad-purchasing. Workers often conduct reports and post insights on the future of data management and customer acquisition, providing customers with a top-level view of various industry verticals. That perspective is no doubt helpful for the company’s enterprise customers, including Duracell, JetBlue, and Dow Jones.

Key Features:

• Advertising data integration
• Taxonomy and classification permission tools
• Unique ID via Oracle ID Graph
• Audience analytics reporting
• Post-campaign analysis

Pros:

• Is equipped with over 200 integrations
• Customers can access offline data with the solution
• It natively integrates with Oracle ID Graph for third-party data access

Cons:

• The solution is primarily a B2C tool with limited B2B capabilities
• Usability and interface clunkiness are common pain points among users
• Because it is part of a larger package, deployment is more difficult

Pricing: The Oracle CX Marketing bundle starts at $2,000 per month for up to 10 users.

Nielsen Marketing Cloud

Nielsen Holdings Inc. is best known for the Nielsen TV ratings, a standard in audience measurement. It’s only right that one of the largest marketing measurement companies in the world has a proprietary DMP. Nielsen Marketing Cloud’s biggest differentiator is its integration with actual Nielsen audience data.

For additional context into just how rich that data set is, consider the fact that Nielsen operates in over 90 countries. Throughout those 90 countries, the conglomerate covers more than 90% of the global population. That plethora of data proves useful, especially when considering that Nielsen Marketing Cloud had some of the best reviews we came across in our research.

Key Features:

• Real-time consumer engagement analytics
• Content marketing, creative testing, search, and social media integrations
• Nielsen AI audience behavior models
• Marketing ROI analysis
• Programmatic purchasing

Pros:

• It pulls from authorized Niesel audience data, a robust data set
• The R&D 100 Award committee has recognized the solution as an innovative product
• It utilizes AI and ML more than its competitors

Cons:

• Although Nielsen audience data is available, some users report feeling restricted in exploring other data sets
• The solution comes with a steep learning curve
• Users also report performance issues regarding load times

Pricing: Nielsen does not share pricing plans for Marketing Cloud with the public. Businesses must contact Nielsen directly for a quote based on their needs, desired features, and company size.

The Trade Desk

Since its founding in 2009, The Trade Desk Inc. has served as a global leader for digital ad buyers looking to run data-driven advertisements. The company’s ethos is a major factor behind its multitude of industry-titan partners, including ABC, Viacom, and The Wall Street Journal.

Iteration is at the forefront of company operations. The platform itself recently went through a redesign, bringing along a more user-friendly interface. With this change comes the company’s proprietary AI engine: Koa. The Trade Desk leverages these new changes to set enterprise campaign goals, set KPIs, and achieve these points more efficiently than competitors. 

Key Features:

• Real-time consumer engagement analytics
• Content marketing, creative testing, search, and social media integrations
• Nielsen AI audience behavior models
• Marketing ROI analysis
• Programmatic purchasing

Pros:

• This DMP comes with a diverse selection of data to pull from
• Customers claim campaign reporting is seamless in both setup and presentation
• Users are provided a Unified ID which makes tracking more efficient

Cons:

• Although reporting is easy to run, users report a lack of granularity
• Customer support can be slow at times
• New users report difficulties in learning the software

Pricing: The Trade Desk does not share pricing plans for its DMP with the public. Businesses must contact The Trade Desk directly for a quote based on their needs, desired features, and company size.

Google Marketing Platform

There is no sign of Google slowing down. Just last year, the company’s advertising business saw over a 43% increase in revenue in Q3 of 2021 alone. This is due to the continual growth of Google Marketing Platform, Google’s online advertising platform aimed primarily for enterprises and large advertisers.

Note that of this entire list, this DMP is the only one that offers complimentary features. Google Analytics, Data Studio, Optimize, Surveys, and Tag Manager are all viable solutions to jumpstart an enterprise’s purchasing journey with Google’s DMP. Businesses can then purchase Google’s more advanced 360 line of products, all of which help run digital media campaigns and gain real-time insight into customer behavior.

Key Features:

• Real-time consumer engagement analytics
• Cross device capabilities
• Google Cloud integrations
• ML powered campaigns via Smart Campaigns
• Programmatic ad optimization

Pros:

• The DMP is very convenient for enterprises that do much of their advertising on Google
• Users can choose various Marketing Platform products to purchase rather than buying an entire bundle
• It takes full advantage of Google’s web data and analytics capabilities

Cons:

• Integrations with third-party sources are rather lackluster
• Users in developing countries claim that the service is limited in support for their market
• Channel management features are reportedly stronger in alternative platforms

Pricing: Google does not share pricing plans for its Marketing Platform package with the public. Its Campaign Manager 360, Display & Video 360, Search Ads 360, and Analytics 360 modules all have separate costs. 

Businesses must contact Google directly for a quote based on their needs, desired features, and company size.

Mapp Cloud

Mapp Cloud, formerly known as Mapp Digital, is one of the oldest players on this list. Founded in 1998, its legacy standing and reputation are well deserved. With customers like CBS, Unilever, and Pepsico, Mapp Cloud is a tried and true DMP that helps enterprises with customer acquisition and engagement.

The company’s main selling point is its “insight-led” approach to digital marketing. This approach helps enterprises combine data with AI to produce real-time insights and connect them with consumers. This helps enterprises connect with customer data throughout different points of the user journey rather than just a pocket of time. Mapp also offers extensive integration support for CRMs, DSPs, and eCommerce tools, all of which come with onboarding and installation support.

Key Features:

• Cross-channel marketing execution
• Predictions, recommendations, and churn prevention
• Predictive customer behavior and insights
• Real-time, unified customer profiles
• ROI analytics

Pros:

• The customer service team is quick to respond and proactive in problem-solving
• It integrates with a variety of third-party tools like Amazon Advertising and Instagram
• It offers solutions specifically designed for different industry verticals, including retail, finance, and agencies

Cons:

• Some users report its email marketing and HTML creators occasionally suffer from bugs
• The interface is not as user-friendly as its competitors
• Complaints about its social media and SMS capabilities are common

Pricing: Mapp does not share pricing plans for Mapp Cloud with the public. Businesses must contact Mapp directly for a quote based on their needs, desired features, and company size.

Read next: Top 8 Data & Data Analytics Trends for 2022

The post Best Data Management Platforms (DMP) appeared first on Enterprise Networking Planet.

Because AI and ML are becoming so ubiquitous, enterprises must be aware of the seven trends directly affecting their operations and future moving into 2022. These trends will not only affect the more tangible, business-side of operations, but also point towards more abstract, ethical questions surrounding AI.

Cybersecurity

Cybersecurity concerns are an inevitable consequence of AI’s rise. AI-backed technologies, such as hyperautomation and 5G, all have security implications that only further these concerns. As enterprises process more and more data, they will need to adopt greater cybersecurity vigilance, which will be aided in large part by AIOps.

Cybersecurity companies are also keeping pace with these increasing threat areas and are utilizing AI and ML to help combat malicious attacks. Leaders in this space—including NortonLifeLock, CrowdStrik, and Darktrace—use AI to learn from previous attacks to help prevent any future compromises. Because most of these software solutions are hands-off, they are affordable and scalable — helping to fuel greater adoption of AIOps platforms in coming years. 

Hyperautomation

Hyperautomation is the identification and automation of as many processes as possible. Many of the solutions adopted under hyperautomation, such as Microsoft Power Automate and Laiye RPA, are AI-focused. An example  of the crossroads between hyperautomation and AI is robotic process automation (RPA) tools, which use bots and automate simple, routine processes within various software applications.

There are two advantages hyperautomation and AI can bring for businesses: employee upskilling and business efficiency. This is primarily due to the growth of low-code and no-code solutions adopted under hyperautomation to ensure everyday users have access to more advanced techniques and skills than ever before. 

Read also: Bringing Hyperautomation to ITOps 

AIOps

As we mentioned previously, one of the primary issues IT leaders and enterprises will face is the growing quantity of data they must deal with. AIOps can assist IT teams with mitigating outages, organizing data sets, and optimizing performance issues.

Enterprises will particularly find AIOps useful for the modern, remote workspace. AIOps technologies can help remote companies in three main ways:

• Visibility: Company-wide visibility was heavily impacted by the work-from-home transition. Enterprise and key business leaders have lost the ability to oversee operations, but AIOps seeks to repair this. IT teams can, for example, track application activity to ensure each department has access to the right tools. 
• Help desks: Traditionally, IT teams must tackle software issues on a case-by-case basis. With AIOps, employees can issue tickets and have their problems automatically responded to and fixed. If issues are too complex for automation, of course, AIOps solutions can alert your IT team. Still, this is a vast improvement to the existing model.
• Application errors: AIOps leverages both AI and ML to identify and learn from previous application errors. This way, IT teams do not have to repeatedly deal with tickets. Instead, these issues can be automatically diagnosed, and even prevented altogether.

Low-code and No-code Solutions

As more businesses undergo digital transformation a prominent barrier to adopting AI solutions is the lack of AI developers and engineers. These are two of the most sought after skills to have in the current technology job market and going forward. 

To combat this, low-code and no-code technologies have grown exponentially. These solutions help users develop complex AI-driven systems with very simple interfaces. Because low-code and no-code solutions are built on bringing previously advanced skills to a wider group of people, employees from various industry verticals will find growth in their skills. By extension, enterprises will see greater business efficiency.

Read also: Using Low-code to Deliver Network Automation

Metaverse

The metaverse is an umbrella term for the online spaces individuals use to interact in a more engaging and immersive way compared to existing modes of communications.

Enterprises and businesses can expect the metaverse to shape their operations in three ways:

• Building new modes of customer and business relations
• Ushering in new currencies and transaction types, such as cryptocurrencies and NFTs
• Streamlining remote employee communications.

AI Ethics

Businesses and enterprises are keen to understand the practical benefits and consequences of adopting AI. However, this interest is tempered by ongoing questions about the ethical implications of AI.

AI posits a number of ethical dilemmas, such as its data privacy challenges and its use to spread disinformation. Even though it might not seem directly tied to the more actionable aspects of running an enterprise, it’s critical that business leaders understand and grapple with these implications.

The adoption of AI also impacts workplace dynamics, with many wondering if its rapid adoption might eventually see it replace humans. It’s essential  to have employee buy-in when adopting AI as a service to explain how the technology will be used and to allay any of these fears.

Industry-wide Shifts

Finally, expect AI to transform a variety of different industry verticals not only in 2022 but throughout the entire decade. Here are a few examples of how AI will continue to shape some of the biggest industries in the market.

Healthcare: The healthcare industry has continually been at the forefront of AI adoption. Leaders in the space will continue to leverage AI to analyze patient data and gain greater accuracy in their diagnoses as well as potentially use that data to discover new drugs.

Customer service: AI is being used in the customer service space for use cases far beyond automated voice messaging. Chat-bots that learn from previous customer behavior and leverage customer data are tailoring the customer experience in 2022. Customers are gaining customized and instant service with AI.

Marketing: Social media and even legacy marketing firms are leveraging AI to learn from past campaigns and tailor future ones. AI-powered marketing can help businesses understand their customer base more and to present more effective campaigns.

Read next: Effectively Implementing AI as a Service

The post Top Business AI Trends to Watch appeared first on Enterprise Networking Planet.

Wider Enterprise Adoption

Netskope reported that enterprises use an average of 1,071 cloud services for their operations. Top solutions, such as Salesforce, have experienced unprecedented growth—ballooning from $161 billion in January 2020 to over $250 billion the next year.

Enterprises should ensure that this rapid adoption does not bypass IT and other business leaders. It’s easy for key enterprise stakeholders to lose oversight of which tools their enterprise has adopted. This is especially true as many businesses have shifted to remote work models. One way enterprises are tackling oversight is through the adoption of AIOps. Ironically, many solutions used by enterprises that employ AIOps in their business operations are SaaS products themselves.

The upside to this newfound ubiquity will be general employee upskilling. As hyperautomation and digital transformation help influence the SaaS space, expect to see more enterprise employees becoming well versed in industry standard tools.

Regardless, the wide adoption of SaaS applications for enterprises is becoming an industry standard. Much of this can be attributed to ongoing business digital transformation and the general acceptance of automated business operations. 

Read next: The Evolution of Data Centers Lies in Digital Transformation

Increased Cybersecurity

It is becoming increasingly apparent that enterprises take on a level of vulnerability when leveraging SaaS solutions. Because most SaaS platforms operate through cloud computing and networking, data centers and IT infrastructures could face an increase in cyber attacks.

These concerns are rising as the Internet of Things (IoT) and 5G adoption introduce new  vulnerabilities. Moving forward, enterprises must prioritize cybersecurity by putting it at the forefront of their operations and creating actionable steps to mitigate threats.  

Writers Tom Wheeler and David Simpson advocated for new approaches to cybersecurity in their 2019 Brookings report, noting how enterprises and individuals must adopt a “new cyber duty of care.” The cyber duty of care calls for prioritizing security in the DevOps cycle, adopting advanced solutions to handle complex attacks, and sufficiently investing resources into cybersecurity for businesses. This is a tangible step enterprises should consider going into 2022. 

New Methods of Oversight

As we mentioned earlier, IT executives are struggling to efficiently oversee their business operations as the global workforce permanently moves to working from anywhere. This struggle extends to overseeing the amount of SaaS applications enterprises are adopting.

A Pulse Q&A report shows that 56% of IT executives still rely on traditional means, such as internal tools and even manual spreadsheets, to manage their SaaS applications. Furthermore, only 41% of IT teams are able to address SaaS application management beyond basic license tracking.

This means that both the methods upon which IT teams track their SaaS applications, as well as the breadth of their methods, is lacking. This is a pain point that should be prioritized by both SaaS platforms and enterprise leaders moving into 2022.

Artificial Intelligence as a Service

Artificial intelligence (AI) as a service is essentially a branch of SaaS. Think of it as SaaS driven primarily by AI and machine learning (ML).

AI as a service will no doubt be a priority for AI-driven enterprises moving forward into 2022. In fact, enterprises are already leveraging AI for three main use cases:

• Cybersecurity: AI cybersecurity is one of the fastest growing sectors in the AI space. Enterprises are using these solutions to learn from human behavior and prevent breaches from ever occurring.
• Automate tasks: Task automation is one of the more practical applications for AI as a service. By utilizing robotic process automation (RPA) software, enterprises can deploy bots into third-party applications and effectively scale their operations.
• Virtual Assistants: Another practical application of AI as a service, virtual assistants are very helpful for enterprises looking to automate and optimize customer support. Wait times can be cut as a whole, and customers can get the necessary help they need.

Although the application of AI for enterprises is exciting, there are a number of challenges enterprises must be ready to face. These include integration, employee buy-in, and cost. Expect the wider adoption of AI as a service to address these challenges moving into 2022.

Read next: Effectively Implementing AI as a Service

Top SaaS Platforms for Rightsizing

Finally, enterprises must be aware of the actual tools that are growing in popularity when it comes to enterprise rightsizing, which refers to the idea of reducing spend and simultaneously increasing value and efficiency from SaaS applications.

Currently, according to the aforementioned Pulse Q&A study, three main players in the SaaS space are at the forefront of rightsizing for enterprises:

• Office 365
• Salesforce
• ServiceNow

Not only should enterprises educate themselves on these tools, but also prepare themselves to use newer and evolving platforms in this sector as well. Some of the other tools IT executives identified as being prime for rightsizing included Workday, Dropbox, and G Suite.

Going into 2022, CIOs and enterprise stakeholders must work on their rightsizing strategies. Various factors, such as application contracts, login data, and user engagement data, will become increasingly important. It’s no surprise that many of the tools that are popular for rightsizing offer enterprise pricing packages and prioritize user-friendliness.

Read next: Saas: Top 5 Challenges and Rewards for Enterprises

The post SaaS Will Continue to Transform Enterprises appeared first on Enterprise Networking Planet.

What are 5G-Powered Businesses?

To understand how 5G will shape enterprise operations, it is important to understand what shapes 5G-powered businesses.

“The 5G-powered business is a business that leverages 5G to transcend the possibilities of today, that uses 5G as a toolbox to solve business problems in new ways, and represent a new way of working and thinking,” says Dr. Brenda Connor, Director of Security Portfolio Application, Ericsson.

There are a number of key differences between last-generation 4G and 5G, including:

• Faster data transfer rates
• Global internet coverage
• Up to 90% more energy efficiency per traffic unit

Perhaps the most actionable benefit 5G can provide for businesses moving forward is its advancement of IoT devices. Businesses can gain the power to offer services that would’ve previously been too expensive to operate. Although this is exciting, 5G’s benefits conversely pose some cybersecurity risks that must be addressed.

5G Cybersecurity Risks

There are four main risks enterprises face when adopting 5G technology. These include the transition from hardware to software-based networks, the rise of IoT devices, the risk of availability compromise, and the lack of end-to-end encryption early in the connection process.

From hardware to software

The primary security risk 5G holds is in its transition from centralized, hardware-based switch to its more distributed, software-based digital routing. According to a 2019 Brookings report, the opportunity for choke point inspection and control is far more limited in a 5G-defined network.

Because 5G will be mostly an all-software network, updates will also be carried out through software— similar to how operating systems on tablets, phones, and computers are updated—an additional point of vulnerability.

Internet of Things

The lack of security in many IoT devices is an ongoing concern. 5G accelerating the world of IoT can only further this risk. Acts have been made to prevent this in government agencies, but enterprises and the private sector still lack these measures.

A Trend Micro and GSMA Intelligence report showed that out of 63% of enterprises that have deployed IoT, 15% have not updated their policies to establish a “security first” strategy. This could be a consequence of the rapid growth of these technologies, but many enterprises and users are seemingly expecting IoT and 5G solutions to be secure-by-design.

Availability compromise

Availability compromise refers to the notion that total network access can be completely cut off through a cyberattack. If enterprise infrastructures are all on a single 5G network, any attack to that network could compromise all facets of the enterprise.

For additional context, this could prove detrimental for national security. If governments do not diversify their 5G networks or use non-overlapping technologies, any attack to the defense infrastructure could prove devastating.

Lack of encryption

Although end-to-end encryption has potential in a 5G-driven network, malicious players can still gain access to devices early in the connection process. Attackers can move laterally and cause more damage from compromising just one 5G device.

Ultimately, increasing the number of objects that are not only online but also integrated with one another on a single network will invariably increase vulnerabilities.

Also read: Approaches to Cybersecurity in 5G-driven Enterprise Networks

Mitigating 5G Cybersecurity Risks

The risks of adopting 5G seem too large to manage at times. Although governments are trying to prepare for the future of a 5G-driven world, enterprises must look for actionable ways to mitigate risks.

Looking forward, enterprises need to prepare a robust 5G security plan. Plans will look different for many businesses, but being proactive about your plan and adopting new enterprise cybersecurity solutions can be a good starting point.

In their Brookings report on new approaches to 5G cybersecurity, former FCC chairman Tom Wheeler and Pamplin College of Business professor David Simpson map out two distinct recommendations for enterprises, governments, and general users to follow as 5G technology continues to advance.

Cyber Duty of Care

The first point both writers make is for companies to recognize and be held responsible for a “new cyber duty of care.” They pull from the traditional idea that common law advocates for: Those who provide products and services have a duty of care to identify and mitigate potential harms that could result.

In a sense, this recommendation goes beyond prioritizing cybersecurity in your company culture. It advocates for inserting security in the DevOps cycle, adopting AI-driven technologies to handle more complex attacks, and generally investing resources into cybersecurity for businesses of all sizes.

Furthermore, the cyber duty of care calls for reversing the historic underinvestment cybersecurity has so far faced. This is especially critical for enterprises that could put public safety at risk if an attack ever was to occur.

Another poignant example of the cyber duty of care is their urge to implement machine learning and artificial intelligence at the core of cybersecurity moving forward. There are a number of AI cybersecurity software solutions already in place that enterprises are taking advantage of. It’s critical to use these tools that can learn from and analyze mass quantities of data that traditional methods can’t keep up with.

The New Cyber Paradigm

Wheeler and Simpson also make the case for a new approach to the relationship between businesses and government. Innovation simply needs a faster approach as the new age of 5G is ushered in. The writers propose a few considerations, including:

• Inspection. Wheeler and Simpson advocate for increasing certification of important network and infrastructure devices. The FCC has historically certified that cellphones, baby monitors, and any other radio-signal-emitting device does not interfere with the nation’s airwaves. This approach should be taken with 5G networks and cyber-vulnerable equipment.
• Consumer transparency. Consumers have little to no insight in making an informed market decision when it comes to 5G devices. It’s important for all parties to be aware of the threats behind 5G cybersecurity, and consumers being given the tools to make informed decisions could help with that.
• Marketplace shortcomings. In what could be the most actionable consideration for enterprises, Wheeler and Simpson note that businesses that take monetary action associated with cybersecurity should in no-way be penalized by those who don’t. To make sure everyone is on the same page, a rewards-based system could help push non-convinced enterprises to take cybersecurity far more seriously than they would otherwise.

The Future of 5G Cybersecurity

Ultimately, the widespread adoption of 5G will most likely see enterprises iterating on how they go about their cybersecurity mitigation efforts. IT teams will have to prepare for identifying and mitigating threats while keeping the user experience and network latency intact. 

Generally speaking, enterprises should be prepared to adopt a hybrid approach to their cybersecurity. Enterprises should uphold cybersecurity in all facets of its operations and company culture. In parallel, they should be prepared to work with advanced cybersecurity solutions as their network of IoT devices expands.

Read next: Understanding the Zero Trust Approach to Network Security

The post 5G Cybersecurity Risks and How to Mitigate Them appeared first on Enterprise Networking Planet.

There are key benefits that data democratization can bring for enterprises. Understanding what data democratization is, its benefits, industry trends, as well as key strategies will provide more clarity for enterprises moving forward.

What is Data Democratization?

Data democratization refers to the accessibility of data throughout all departments of a business. Historically, IT departments had access to data and were gatekeepers for any marketer, analyst, or business leader in need of said data.

The adoption of data democratization has come in parallel with the rise of low-code solutions and software such as customer data platforms (CDPs). It shares  many similarities with the concept of DevOps, . which aims to bridge the communication gap between development and IT operations.

Also read: Powering Digital Transformation with Customer Data Platforms

Data Democratization Benefits

There are a number of benefits the implementation of data democratization can provide for enterprises. It’s important to identify which benefits are most valuable for your enterprise. 

1. Customer Intent

As more artificial intelligence (AI) tools are being adopted by enterprises in their respective digital transformations, customer intent is becoming easier to identify.

Congruent to this change, data democratization can provide a wider breadth of customer intent. This is because data is being analyzed and leveraged by multiple departments, all with different philosophies and approaches.

Ultimately, this benefit is reliant on a company culture that allows different departments to experiment and approach this data with their unique skill sets.

2. Efficiency

Tools such as AI analytics and cybersecurity software are built on data democratization. As enterprises continue to adopt these tools to house their data in a single and accessible location, the efficiency these individual tools bring is engrained in the company’s operations.

On a wider scale, data democratization is built on enterprise departments genuinely understanding the data they have access to. This allows your development team to truly grasp the issues various internal departments are facing. This minimizes confusion and builds efficiency.

3. Customer Experience

Because data democratization brings a wider scope of customer intent as well as greater operations efficiency, customer experience is naturally improved.

An actionable example of this is customer-facing departments having access to preferred contact and previous shopping data. This allows your sales team to provide tailored customer experiences and service.

Data Democratization Industry Trends

There are three main trends that data democratization could usher in for enterprises. These include the increase of low-code solutions, the transformation of customer-facing roles, and employee upskilling.

Low-Code Solutions

Because many of the software solutions enterprises are adopting are built on data democratization, their interfaces and operation require little to no development experience. Many of these solutions are considered “low-code.”

Low-code solutions are user-friendly solutions that present data sets and application creation capabilities to the everyday user. Although developer tools are still offered in low-code solutions, their usability will surely be leveraged parallel to the rise of data democratization. Paired with the growth of various technologies such as AIOps and IT automation software, expect to see a rise in these types of solutions.

Customer-Facing Roles

As previously mentioned, data democratization can shape the way customer-facing roles such as help desk employees and sales teams approach their customer experience. 

Having vital information about a customer, such as their preferred contact method or whether they’ve submitted a ticket before, can transform the ideal customer experience altogether. ata democratization can also ensure multiple facets of your organization are sharing their vision of what the ideal user journey could look like. Data democratization opens up new doors for iterating on customer experience as a whole.

Upskilling

Finally, especially with the rise of hyperautomation and digital transformation, expect to see upskilling across enterprise employees. Employees will need to learn new tools that assist them in both their individual job requirements as well as interdepartmental collaboration. Again, this can be seen through the rise of low-code solutions, as previously mentioned above.

Also read: Bringing Hyperautomation to ITOps

Data Democratization Key Strategies

1. Company Culture

Much like any other digital transformation, enterprise company culture must advocate for data democratization and cultivate a space where employees can collaborate.

Employees naturally being upskilled due to new technologies and AI solutions could make fostering this type of culture easier to accomplish. Furthermore, employees should feel they are in an environment where they are learning the full impact of the data sets they are working with, as well as the various applications of said data.

Moving forward, users with little to absolutely no data analytics experience will grow more confident with their findings and contribute to enterprises in ways never before seen. Fostering a company culture that upholds this future is a vital first step in any enterprise’s strategy.

2. Establish Stakeholders

Although access and understanding will be open to all with data democratization, key stakeholders and leaders need to be established throughout your enterprise to make strategic decisions.

This is where a company’s DevOps and AIOps strategies  will truly come to fruition. Are there key stakeholders overseeing relevant processes in your data democratization strategy? Enterprises will find that cases will differ, but having effective DevOps at the core of your business could significantly help with this strategy. 

3. Uphold Communication

One of the primary concerns of data democratization is misinterpretation and communication of data. Although fostering a company culture that helps teams understand the data they have access to can help, interdepartmental communication still must be at the forefront of any data democratization strategy.

Teams must uphold communication and share their interpretations about data sets to gain a multifaceted view. Your data-based strategy might make sense until the IT department and customer-facing team suggest counterpoints or their own vision. 

Much like when you’re establishing key stakeholders, companies with robust DevOps strategies will find more success in this step than others. In many ways, data democratization could be considered a natural progression from DevOps. This will be accelerated even more so by the rise of AIOps technologies in the near future.

4. Don’t Over Rely on Solutions

Data democratization is exciting. So are the growing number  of solutions dedicated to it. However, solutions should never act as replacements for your responsibilities.

Think of AIOps, cybersecurity, and analytics tools as helpful assistants that can store data in an easily manageable and accessible manner. They can even provide insights from highly advanced machine learning and AI technology. 

Ultimately, however, human analysis is essential to any data democratization strategy. The basis of it relies on the various interpretations different departments in enterprises can extrapolate. Solutions can be of great assistance to this, but should never act as an “end all, be all.”

Read next: Best Data Analytics Tools & Software 2021

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Artificial intelligence (AI) has increasingly moved to the forefront of societal, economic, and even ethical debates about our future. Although the technology behind AI continues to grow, its potential often overshadows its practical applications for enterprise businesses. This is partially the reason only 14% of firms have deployed AI in production. Here are some practical methods on effectively implementing AI as a service for your business.

Build Foundational Knowledge of AI

Learning about the advancement of AI and its applications seems like a daunting task, however, there are many resources available for learning about AI’s history, and its modern day applications. 

AI Knowledge Resources

There are a number of resources available for enterprise business leaders, such as CIOs and CTOs, to learn more about AI. Courses such as those provided by DeepLearning.AI or Coursera can offer business-side information on AI and its practical implementations.

In addition to learning about the history and current landscape of AI, it’s important to understand its different applications. Google AI offers a number of top-level, free guides that cover important AI applications. These include applying AI for social and environment change, as well as designing AI products and implementation in a human-centered way. 

Employee Buy-In

Although key team members and leaders in your organization need to have a foundational knowledge of AI, enterprise businesses must ensure that their employees understand the value AI can bring to their jobs as well.

One of the most prominent barriers in enterprise businesses adopting new technologies is garnering employee buy-in. AI is a particularly challenging topic to tackle because of its seemingly uncertain future and its perceived threat to job security. These concerns are valid and can be addressed in a number of ways:

1. Education: Being thoroughly educated on the landscape of AI and its future means leaders can better communicate how it will play a role for their company and employees. This education should be at the forefront of the company’s digital culture.
2. Company Culture: A fundamental part of gaining employee buy-in is fostering a company culture that is forward thinking and innovative. For startups and tech companies, this might already be the norm. However, legacy companies might have a more difficult time making this transition. An effective way to jumpstart this process is upskilling employees.
3. Upskill Employees: Employees do worry about AI replacing their jobs. In reality, AI’s implementation as a service will assist and better employee capabilities, rather than totally replace them. The best way to help employees understand this is to provide them with hands-on experience. Employees deserve to spend time and training with the tools that will become an integral part of their company’s operations.

Equally important as understanding AI and garnering employee buy-in, is building an understanding of the problems your business faces that AI could potentially address. A 2020 IBM survey of over 4,000 US, EU, and Chinese businesses showed that cybersecurity, task automation, and virtual assistance are the top use cases for AI. Let’s look into how AI can be leveraged to tackle these challenges.

Leverage AI for Cybersecurity

One of the fastest growing avenues for AI implementation is cybersecurity. Cybersecurity companies use AI to detect malware and potential attacks. Advanced solutions train themselves and learn from human behavior to prevent breaches from ever happening. Cybersecurity tools built with AI can read more data in a timely manner, allowing for business scalability.

The AI cybersecurity space is only growing. Newer players like Deep Instinct are tapping into the more advanced capabilities of AI and machine learning (ML) to create an autonomous, yet highly powerful solution for enterprise businesses. 

Enterprise businesses should especially consider implementing AI cybersecurity as new frontiers such as the metaverse and crypto currencies grow into the mainstream. These new technologies are exciting, but could put businesses lacking proper cybersecurity in a vulnerable position. We suggest enterprise businesses also catch up on the pros and cons of implementing AI cybersecurity to better familiarize themselves with the space.

Also read: Best Network Security Software & Tools of 2021

Automate Tasks

The most practical application of AI as a service is automating repetitive administrative tasks. This implementation of AI allows for businesses to simultaneously scale and cut costs.

One example of this is Robotic process automation (RPA) software. RPA software allows enterprise businesses to deploy bots into third-party applications to automate tasks. RPA software allows for a variety of use cases, including extracting unstructured data, opening and moving files, and completing keystrokes.

Also read: Top RPA Tools 2021

Virtual Assistants

Virtual assistants and chatbots are very effective implementations of AI, especially for enterprise businesses looking to optimize customer support. Because these solutions are automated, wait times are effectively cut and customers are able to get answers immediately.

Although there might be worries about losing the human quality behind customer service, chatbots and AI are continuing to improve listening tools as well as personalized web visits for customers. In fact, the conversational AI realm is growing just as fast as the AI cybersecurity space.

Virtual assistants are build for a number of different industry verticals, including:

• Contact centers
• Insurance
• Financial services
• Healthcare
• E-commerce

Not only can conversational AI platforms assist enterprise businesses with their customer relations, but also with internal employee tasks. Solutions such as Aisera include virtual assistants that act as 24/7 support systems for employees to finish onboarding, or perform more clerical tasks such as signing up for insurance and retirement plans.

The Challenges of AI

As we’ve seen, there are many practical applications that enterprise businesses can adopt to implement AI as a service. Still, there are challenges executives face that could prevent AI implementation in the first place.

According to Deloitte, one of the biggest challenges enterprise businesses might face is integration with existing processes and systems. Luckily, many companies developing AI solutions understand this, and offer both onboarding assistance and native integrations in their services. 

Another challenge that was previously mentioned is employee buy-in. As with many other digital transformations, garnering the trust and support of your employees in implementing AI as a service could prove difficult. This is especially true for legacy enterprise businesses. Ultimately, it’s the responsibility of key business leaders to foster a company culture that welcomes these new technologies.

Finally, the last challenge is cost. Many executives feel technologies and expertise are too expensive. Although implementing AI definitely comes with a hefty price tag, enterprise businesses must take into consideration the level of scalability it brings. 

By implementing cybersecurity, automating tasks, and adopting virtual assistants, enterprise businesses can ultimately cut costs and focus on scaling their businesses effectively and efficiently.

Read next: The Impact of AI on Unified Communications

The post Effectively Implementing AI as a Service appeared first on Enterprise Networking Planet.

What is the Metaverse?

The metaverse generally refers to online spaces where humans can interact in a more engaging and immersive way compared to our existing modes of communications. A primary example of this is virtual reality (VR) headsets. 

The metaverse has typically been associated with multiplayer online games, but can now encapsulate video conferencing, social media, and live streaming. As this realm continues to expand, so will the possibilities of personal identity, content creation, and even virtual economies.

Regardless, many players in the financial and tech space have different ideas of what the future of the metaverse holds. Enterprise businesses will be most interested in its potential to radically change how businesses interact with their customer base.

How can the Metaverse Help Enterprise Businesses?

It’s fair to have questions about the practicality of the metaverse. There are three primary ways the metaverse can help enterprise businesses:

• Creating new spaces for customers to engage with businesses and their products
• Allowing new currencies to enter the marketplace on a mainstream scale
• Creating new communicative tools for employees to work together

It’s important to discuss each point and properly weigh their worth for enterprise businesses.

Customer & Business Relations 

The first and most likely frontier of the metaverse is creating new spaces for enterprise businesses to sell their services. Perhaps the most striking example of this is the Sotheby’s Metaverse. This is an online marketplace where individuals can browse and purchase NFT art pieces.

Corporate interest in the metaverse is invariably growing. Roblox and Fortnite, two popular online games, are making the transition from being seen merely as video games to actual expansive worlds. Dave Baszucki, Roblox’s co-founder and chief executive, believes that Roblox can stand as the next frontier for business communication. Of all the practical benefits the metaverse can provide for enterprise businesses, online marketplaces are very likely. Conversely, they might be hard to immediately adopt. 

Enterprise businesses must ultimately take their customer base into consideration. If you’re in the tech realm and feel a portion of your customers are already familiar with these concepts, strategizing how to build a presence in the metaverse could serve as an effective roadmap for the future.

Also read: What is an NFT?

New Currencies

With the rise of blockchain-based cryptocurrencies, coupled with the fact that most metaverse platforms run on blockchain technology, enterprise businesses can sell their services on an entirely new marketplace. While crypto is undoubtedly becoming a mainstay in the global marketplace, the metaverse embraces it more.

In addition to its own aforementioned metaverse, Sotheby’s opened an NFT gallery in Decentraland—a decentralized metaverse. This means that decisions are not made on a top-down basis. Decisions are instead made by users who occupy Decentraland themselves. A key factor in this decentralized experience is Decentraland’s official currency: MANA.

The Decentraland metaverse is a key example in how new currencies can emerge and drive new business. MANA has been used in transactions that have totaled more than  $900,000. Users can decide how to use their MANA in this metaverse: to either buy NFTs and virtual properties or to gamble for more in virtual casinos. 

Examples like this help bridge the gap between real-life business operations and the metaverse. If companies like Gucci and Sotheby’s can successfully translate their business models to the metaverse, enterprise businesses should start ideating on how they can do the same. This trend will only continue to grow as crypto currencies are more accepted in the mainstream.

Enterprise Employee Collaboration

Although the metaverse’s monetary benefits are important for enterprise businesses, the metaverse also allows for new modes of collaboration. As we’ve noticed during the pandemic, collaboration over Zoom is convenient yet oftentimes limiting. The metaverse can maintain the convenience of video conferencing while simulating the effectiveness of physical meetings by creating digital conference rooms. 

Two companies at the forefront of bringing employee collaboration to the metaverse are Facebook and Zoom. In fact, both companies recently announced new tools dedicated to creating a more authentic hybrid work experience. 

Facebook’s Horizon Workrooms can be downloaded by anyone who owns an Oculus VR headset. In Workrooms, users can share their screen, write and draw on a shared whiteboard, and leverage spatial audio to make conversations feel more authentic. Zoom is integrating Workrooms with Zoom Meetings and Zoom Whiteboard.

Also read: Zoom Rolls Out New Tools, Features for Hybrid Work

Are There Risks for Enterprise Businesses Adopting the Metaverse?

There are two primary risks for enterprise businesses adopting the metaverse. The first is the fact that the metaverse, alongside many other blockchain technologies, offers a seemingly unpredictable future.

This notion that the metaverse might not last is accelerated by Bitcoin’s volatility. However, the fact that massive enterprise companies such as Facebook, Adobe, Nvidia, and BMW are investing in its future means that the metaverse is building a stronger sense of legitimacy for the general public. This has taken some time, but ultimately the metaverse has seen more mainstream acceptance when compared to cryptocurrency. 

The second concern that grows with the metaverse’s future is its cybersecurity risk. But again, as the metaverse is adopted by the mainstream, data use ethics and cybersecurity protocols will inevitably be mandated to address all the risks of the metaverse. Still, enterprise businesses should closely monitor any risks involved with adopting the metaverse and other blockchain technologies such as crypto.

Also read: Blockchain Technology Can Have a Starring Role in Cybersecurity

What is the Future of the Metaverse for Enterprise Companies?

As noted, enterprise companies have reason to be skeptical about the metaverse and what it can practically accomplish for their operations. Although some benefits might seem too high-level and abstract to implement immediately, highly successful enterprise companies are investing in its future for its inevitable benefits.

Until then, examples of the metaverse that actively help out enterprise businesses currently exist. This can come in the form of VR gaming, digital art installations and marketplaces, as well as virtual collaboration hubs for employees. We recommend enterprise businesses study these existing models to better familiarize themselves with the metaverse, blockchain technologies, and how transactions can be made in an online environment.

Read next: Top Blockchain as a Service (BaaS) Providers for 2021

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