Data Dynamics, Inc

With the increasing number of files and growth of your unstructured data, gaining business insights through deep analytics, artificial intelligence, and machine learning are only becoming more complex. The value of these files is trapped, and as you generate more each day, they become more expensive to store and support every year.

As initiatives for effective data management solutions have been developing across all enterprises, the value of metadata tagging is also becoming a top priority amongst CIOs. With custom metadata tagging, you can expedite access to your files and maximize your investment by uncovering the value found within your data.

Here are the top 5 metadata tagging mistakes you should avoid.

1. STANDARD METADATA IS NOT ENOUGH

Standard metadata provides information that is enough for a surface level understanding of your data. In order to go deeper, custom tags are required to enrich your heterogeneous data. Custom metadata tagging resolves storage problems by turning old and historic data into valuable and useable information.

When the time comes to create reports and perform deep analysis, you can use your personally identifiable information (PII) to search all enterprise data assets and run semantic classification for data discovery. For this reason, the custom tagging functionality enables you to easily search, discover, and understand your data relationships to get the most value from your data.

2. YOU HAVE NOT AUTO-TAGGED YOUR DATA

Auto-tagging your data allows flexibility by deciding which data sets should be tagged with personalized information. Custom auto-tagging can be done through highly scalable scanning engines based on industry standards of NFS and SMB. APIs are used to scan and collect data sets which are then tagged with your customized information to support deep analysis using artificial intelligence and machine learning. When auto-tagging your data, you establish a glossary of all your data assets. This creates the foundation for effective data governance which results in efficient data management and valuable business insights.

3. YOUR TAGS ARE NOT CONDUCIVE FOR ANALYTICS

Knowing what you have is a great start and adding tags to your data encourages efficiency, but the real value of custom tagging is how it enables your business analytics. After you have tagged and moved your data into Amazon S3 for example, it improves the quality of how you search for files across your systems and data lake. Once you have segregated the required data using the tagged policies, you can then run analytics on Amazon Athena to gain valuable business insights based on your enterprise needs and goals. For that reason, your tags should be conducive for analytics to gain the full potential from your data.

4. TAGS ARE NOT AUTOMATICALLY INTERPRETED INTO COLLECTIONS

Custom metadata tagging enables automated and customized file categorization. By accelerating the mapping of tags to logical data sets, this functionality allows you to classify data according to your enterprise-specific categories. For instance, collections can be associated with a certain project or they can be classified into each line of business such as sales, marketing, or finance.

As a result, it becomes easy and efficient to run analytics on a collection to determine their capacity and the number of resources consumed. Based on the tags for each collection of data, we can analyze the project’s performance or even the output from each enterprise department.

5. TAGS ARE NOT PORTABLE

We have established that custom tags are a significant part of any data management strategy. The main value of tags is that they are a gateway for data analysis and business insights which delivers the biggest return on investment. Ensuring that your tags are portable so that they can run on any platform is key for data analysis. Athena, Kibana, and StorageX are a few platforms utilized for various types of reporting through metadata tags.

Each platform should be able to understand and process your tags for you to gain the insights from your data analysis. Since there are numerous platforms available to extract insights from your data, it is important to use portable tags in your data management strategy for compatibility and flexibility when utilizing various software platforms for deep data analytics.

WITH DATA DYNAMICS, BE THE CHAMPION OF YOUR OWN DATA

Without metadata and custom tags, enterprises cannot extract the deep insights that big data offers. By streamlining the process to collect, integrate, and analyze big data sources, custom metadata tagging empowers enterprises to achieve greater returns by leveraging their data. Since it is an essential part of the data management strategy, Data Dynamics wants to ensure that you are successful when it comes to your metadata tags.

If you want to start your digital transformation today or have more questions, we would love to help. Request a call today and one of our experts will contact you as soon as possible. Or even better, request a demo and see it all in action.

ABOUT DATA DYNAMICS

Data Dynamics is a leader in intelligent file management solutions that empower enterprises to seamlessly analyze, move, manage and modernize critical data across hybrid, cloud and object-based storage infrastructures for true business transformation. Its award-winning StorageX platform eliminates vendor lock-in and provides a policy-based, storage management platform to provide the insight, agility, and operational efficiency to transform your data assets into a competitive advantage.

Used today by 24 of the top Fortune 100 companies, StorageX has optimized more than 160 PB of storage, saving more than 80 years in project time and $80 million in total storage costs.

An organization’s data is considered as the most vital asset to the entire enterprise. It is the foundation of all an organization’s knowledge, possessing information that is necessary to what employees do there. Organizations that don’t understand the importance of their data and how to manage it are less likely to survive in today’s digital world. How can you ensure that you and your organization does not fall in line with the companies making those sorts of mistakes? Easy – it starts with proper Data Management.

Data management is the practice of organizing and maintaining data processes to meet ongoing information lifecycle needs. Effective data management can ensure many positive opportunities for your organization, such as minimizing potential errors, increasing productivity, support for making appropriate business decisions.

Here is a top 5 checklist for enterprise data management that you should implement for your organization in 2019.

1. KNOW YOUR DATA AND WHAT YOU HAVE

Massive data growth is more than just a technical challenge – it is a strategic challenge that can impact your bottom line. Unstructured data that is being poorly managed or lost, become major compliance and legal risk to the company. The challenge you face is understanding what data you have and where it is located. Enterprises require in-depth hardware and file system information to manage their IT business processes. An analysis of all your data across all your systems provides a visualization of the type, age, name, and access behaviors of files to identify your data workloads to differentiate between your critical data from dark data. You’ll need powerful data analytics to tell you what you have in order to convert your data from a risk to a strategic asset.

2. OPTIMIZE YOUR DATA ENVIRONMENT WITH HYBRID CLOUD

Once you have a complete understanding of your data environment, a hybrid cloud strategy can allow data workloads to move between private and public clouds in a flexible way as demands, needs, and costs change. This gives businesses greater flexibility and more options for data deployment, usage, as well as access to data analytics to maximize your investment. With skilled planning and a structured approach, a hybrid cloud can deliver on-demand flexibility, empower legacy systems and applications with new capabilities, and become a catalyst for digital transformation. The result can be an elastic and responsive infrastructure which can quickly adapt to the changing demands of the business.

3. MAKE YOUR METADATA WORK FOR YOU

Finding storage solutions for your data is the first step, but what happens when you now want to extract the value from your data sets through a deep analysis? Adding custom metadata tags to your datasets will help prepare yourself for that day. Without metadata to provide provenance, you have a dataset without context and little value.

By running an integrated file scan with a repository to store all the details on the analyzed file data, you can then add your custom tags to these data sets. This provides an enriched set of metadata from which you can gain insights through reports generated from the metadata repositories. You can now identify and segregate a set of data using metadata tags to create custom reports of your data, enables machine learning and artificial intelligence for a deep analysis of your data. This converts your data into value and makes your metadata work for you.

4. BE IN COMPLETE CONTROL OF YOUR DATA

Digital enterprises are investing to create, store, maintain, and protect their data. Though data sitting idle in storage has no real value, the analysis and business insights gained from data is what makes it worth the price. However, the speed and efficiency in accessing and obtaining that data is more significant since it greatly impacts the value of the data. The ability to access data faster increases productivity and enables you to respond to business requirements faster which translates into higher profits. With a solution that allows you to store your files economically, in native format, and without vendor lock-in, you can be in complete control of your data while it being accessible when you need it.

5. INTEGRATE DATA MANAGEMENT WITH YOUR BUSINESS DECISIONS

With data streaming in from multiple sources, leveraging the full value of your data can be complex but also very rewarding. With a standard process in place to ensure that your data is accurate, usable, and secure, you can generate valuable data-driven insights. This starts with data governance, which provides the guidelines for data security, accessibility, and shared among authorized people. Secondly, ensuring high data quality is key before data integration. Having clean data without duplications and redundancy is necessary when preparing your structured and unstructured data for analysis. Lastly, you need a security policy in place to protect your data and prevent data breaches. With these measures to ensure your data accuracy, accessibility and security, you will realize the power of being data-driven and make business decisions with confidence.

BECOME A CHAMPION OF DATA – WITH StorageX

Data management can play a huge factor in productivity and efficiency, but it may be difficult for companies to immediately start. Before you decide on data management for your company, consider StorageX.

StorageX dynamic file management platform empowers you to analyze, move, manage and modernize your data where you need it and when you need it, from your data center to the cloud. StorageX is built using industry standards and operates completely out of the data path, freeing your data from technology lock-in, complexity and risk. Enterprises who are consolidating data centers and modernizing legacy applications rely on StorageX, the most trusted name in file management.

If you want to start your digital transformation today or have more questions, we would love to help. Request a call today and one of our experts will contact you as soon as possible. Or even better, request a demo and see it all in action.

ABOUT DATA DYNAMICS

Data Dynamics is a leader in intelligent file management solutions that empower enterprises to seamlessly analyze, move, manage and modernize critical data across hybrid, cloud and object-based storage infrastructures for true business transformation. Its award-winning StorageX platform eliminates vendor lock-in and provides a policy-based, storage management platform to provide the insight, agility, and operational efficiency to transform your data assets into a competitive advantage.

Used today by 24 of the top Fortune 100 companies, StorageX has optimized more than 160 PB of storage, saving more than 80 years in project time and $80 million in total storage costs.

August/September 2018 Edition

As corporations prepare for their 2019 annual budget, many enterprises are concerned with how to prepare for their digital enterprise needs, and how those decisions may need to adhere to corporate and industry governance.  Data Dynamics CEO Piyush Mehta, the “Dean of Data,” addressed the specifics on budgeting and governance issues in his recent Mehta-Data^© podcast. 

Why is governance an issue in data management and migration?

There are many aspects to which data governance is looked at because of the sheer amount of data and the importance of that data in every vertical marketplace.  Governance really is encompassed of four key aspects or attributes.

One is availability and the available access to such data for usability. How many people can use the data, and how can it accurately be made available.

The second is content security.  Enterprises need to ensure that their data is correct in terms of its content, and such security ensures that those who need to access the data can do such…and only those that should access the data will have access.

This ties to the third area of unstructured data. The largest portion of data growth comes from unstructured data. Most organizations have 60-plus percent of their data today in an unstructured format.

And, the fourth area is, by far, the most rapidly growing aspect of their data infrastructure, that being regulatory issues.  Changes in regulatory issues challenge every enterprise relative to how they monitor and maintain these regulatory issues.

How do regulatory issues specifically affect the governance of data management and migration?

Primarily, if looked at from a regulatory standpoint, I believe this is the wrong approach.   GDPR in Europe and definitely Sarbanes-Oxley in the US put emphasis on how data is managed and accessed.

An organization really needs to look at data governance more from an internal efficiency standpoint rather than regulations, driving capability in helping it manage its lifecycle. At the end of the day, governance is in place to drive effectiveness and efficiency in the control and management of the data, rather than it being there for administration.

The future of governance security issues are important. But, the challenge is who is accessing data and how.

Does this relate purely to having the proper rights and privileges to access?

As you know, external sources look to pry into data, both personal as well as business confidential information.  The major challenge is whether different departments should or should not have access to proprietary and/or personnel information within a company, which is a key aspect challenge of a business.

This is further complicated by mergers and acquisitions, where you have different access points for different records. Making sure that these are not aimlessly transpired so that management and governance access controls can be limited, is beneficial as everyone moves to the hybrid cloud is imperative to every industry.

How does governance relate to such a hybrid cloud scenario?

At the end of the day, you have to make sure that you do have a team of reliable data stewards. These are the people that are going to be responsible for the overall management of the governance, and this could include and should include both management and contribution lines of business, as well as the information technology teams that can drive the technology aspects.

When you take these data stewards and apply the necessary compliance, whether the data sits locally or it is in the public cloud, or maybe a hybrid model, wouldn’t really matter. Because you are now applying the same standards along with the technology and processes required to manage that data.

How are organizations tackling this governance issue in the big picture you just detailed?

As I mentioned, most people are looking at governance in the wrong way, and see it as more regulatory than internal efficiency driven. When people are running a disaster recovery test as a means of governance, it is done to make sure that it passes to avoid any kind of risk relative to the compliance issues from an external governance body.

When they do this, they actually plan out the entire data recovery (DR) process proactively and ahead of time, rather than just flipping a switch. They just want to determine governance compliance.

Yet, the data can be moved to a secondary site while maintaining the same access as before. This should be embraced because it establishes better management rather than rigorous planning, not because it meets regulations.

At the end of the day, when a disaster happens instantaneously or over a period of time, your organization must be ready.  Make sure that you are embracing governance from a productivity standpoint rather than a checkbox that needs to be done for regulation’s sake.

How can such solutions for a data management organization help address these challenges relative to scale, both geographically and in terms of sheer data volume?

There are three key pillars for data stewards, the first being the area of compliance, and creating the standards which are the processing element.

Second is the technology element and having software solutions that can scale at a global level to deploy and manage the compliance required around these established standards with tens of billions of files, if not hundreds of petabytes of data.

The third is the ability for your software to meet this type of scalability, which is important.  This ties in with the ability to understand and address the security aspects of such.

This availability and accuracy, along with the obvious usability, provides a good technology platform to facilitate governance issues for fiscal and organizational calendar years. And this is where the enterprise budget comes into place.

How can budgeting affect becoming a data enterprise?

The challenge with budgets a continuing game that most large enterprises play.  There is never enough money to address things proactively, but always an open checkbook to correct a problem or challenge reactively when such is considered mission-critical or critical.

It is important to budget accurately for people and time by the data stewards, in terms of establishing and maintaining the proper compliance and standards, and then spending on the software and technologies required to automate, manage, and proactively leverage artificial intelligence to drive a proactive approach to governance. The reactive aspect which most organizations use is when infiltration access to data happens most often.

When a problem occurs, whether it is infrastructure-related or people – related process challenge, enterprises often fund an unimaginable amount of money without hesitation. So, I believe this proactive budgeting plan can avoid most reactive issues.

Based upon what you just described, what should an enterprise be doing right now to prepare for 2019 when it comes time to allocating budget items?

I think it’s important to talk to the right constituents and potential partner experts so that they can put the proper team in place and to align the team to make sure that standards are set in accomplishing a proactive governance program.  Different software platforms can be researched and reviewed to ensure the proper value and technology is acquired to address reactive and proactive compliance of standards.

Partnerships should be fully tested and proven out in order to ensure the proper scale can be utilized to leverage a 2019 implementation plan.  Enterprises should also talk about testing several aspects with available discretionary funds for the rest of 2018 to best determine next year’s budget and solutions acceptability.

How can a company better become a data enterprise without a specific budget allocation?

Small steps can be initiated when initially addressing reactive solutions. It’s hard to deploy them at a global level, but you can talk to companies that offer software platforms which might be tried on a subset of the environment.

It is vital to test these and ensure that such solutions meet or exceed your standards and requirements from a compliance or data governance standpoint to proactively approach the problem in a step-by-step fashion, rather than as a piecemeal conclusion.

Such holistic approaches assist in time and budgetary issues management which can be avoided.

What if people should need additional information about governance and budgeting?

They can find anything online at www.datadynamicsinc.com. We have a ton of information available for them and would be happy to provide further guidance from one of our subject matter experts.

Another quick and easy way is to go to our website at www.datdyn.com, where we have created a survey based on customer responses. What we found is a lot of customers are asking us typical questions that allow and help them to understand where and how they can get to digitalization.

We created the survey right on the top of the website. Take a look, and it can help guide you on the journey, and to how best to digitalize based on the survey responses, and where you’re at in the journey.

If you are interested in moving to the cloud for storage savings and better business analytics, you can get a cost of ownership (TCO) comparison and a list of recommendations by completing a short survey on the Data Dynamics website, www.datadynamicsinc.com for a free assessment.

You can also subscribe to our Soundcloud channel and get access to all podcasts!

Have you experienced vendor lock-in? Is there an easier way to manage and store your data? Data management can play a huge factor in productivity and efficiency. Understand the benefits of StorageX and how you can transition to a rich set of capabilities that are the building blocks to Dynamic File Management for the Digital Enterprise.  

The 7 Benefits of StorageX

1. Analytics: Know what you have and where it is with intelligent views. StorageX provides powerful file analytics to tell you what you have so you can turn your data from a risk to a strategic asset
2. File Migration: With actionable data move your files with ease across any technology. Easily merge with another company and more.   
3. File Replication: Copy files for backup, disaster recovery, DevOps, or performance. Don’t be tied down to one vendor, know that your company’s assets are in good hands.  
4. Archive Retrieval: Even though it is not needed on a daily basis, organize your archived files for easy access. Keep archive data at your fingertips. Search and retrieve data for audits discovery and analytics.   
5. File Archival: Centrally manage data from “live” to “archive” and optimize data placement for compliance needs. Organize your files to make it easy for anyone within your te
   am to find what they need.
6. Namespace Management: Fully utilize Microsoft’s’ Distributed File System (DFS) capabilities from one console. Customize the organization of the DFS namespace to fit your company.
7. Software Developer’s Kit: Integrate dynamic file management into key business application with RESTful API’s. The developer kit features options to integrate data movement with the cloud for file archival and disaster protection.
8. Application Modernization API: Your Applications in control of moving data to the cloud and back. Cloud data done your way. Move files easily across heterogeneous storage resources, placing data where you need and when you need it.

With the facts stated above, it’s evident that Dynamic File Management was created to ease the pain of not being able to access and store files. The benefits of StorageX will lead your company to success and prepare yourself for the cloud.

If you want to start your digital transformation today or have more questions, we would love to help. Request a call today and one of our experts will contact you as soon as possible. Or even better, request a demo and see it all in action.

Enterprises are unable to effectively manage data due to technology lock-in, complexity, and risk. What is technology lock-in you might ask? Technology lock-in is the idea that the more a society adopts a certain technology, the more unlikely users are to switch. For example, the continued prevalence of the QWERTY keyboard layout is said to be caused by technological lock-in. 

The Problems With Managing Data Today

Growth continues to impede an enterprise’s capabilities to manage data. Over the next year, there will be a 59% increase in worldwide data growth. Making it impossible for enterprises to strategically join the cloud. They have also tried to effectively manage data with archaic tools and manual processes – resulting in an IT system that can’t keep up, and not knowing what data they do have. With that being said, enterprises move data from one system to another instead of building value.

Execute a Dynamic File Management Strategy

What can you do to successfully and effectively manage data in the cloud? Utilize the intelligence offered, make sure you’re in control with Dynamic Data for the Digital Enterprise. Analyze your data by knowing what you have and where it is. Have the capabilities to unlock your files and move them with ease. Control, manage and synchronize file resources on demand. Lastly, modernize and always integrate dynamic file management as technology moves forward.   

Be in Control & You Can Effectively Manage Data

Curious about how controlling your data will affect your company? It has been proven that properly managed data increases by 10x and reduces costs by 50%. Unlock your data assets, prevent vendor lock-in, and uncover the true value of efficiently managed data with Data

If you want to start your digital transformation today or have more questions, we would love to help. Request a call today and one of our experts will contact you as soon as possible. Or even better, request a demo and see it all in action.

July 2018 Edition

Many corporations are concerned with the “buzzword” of becoming a digital enterprise so that they can “get to the cloud.”   Data Dynamics CEO Piyush Mehta, the “Dean of Data,” addressed the specifics of how a company can become a digital enterprise in his recent Mehta-Data© podcast. There seems to be a lot of corporate chatter among C-Suite executives and IT professionals at all levels on how does their company become a digital enterprise. First off, what really is a digital enterprise?

“This is an entity that is technology driven across all processes– both internal and external processes– that drive efficiencies and takes things that may have been done with labor-intensive means toward an automated, systematic process. Externally, this relates to how to increase their competitive advantage by accelerating their go to market, by being more poignant in how and who they address within their audience, and by delivering things to their audience.

“All of this centers around being able to leverage different data points that these entities are collecting, and converting them into information that is actionable and valuable to drive that differentiation.”

How do you manage data differently in a digital enterprise versus conventional means?

“First and foremost, to become a digital enterprise you are collecting data across so many facets. Whether they be internal processes related to HR, marketing, or internal accounting, or whether they be external to collecting data on consumers, and how you know their buying patterns.

“For example, where they travel, what are they like to eat, what type of restaurant or the type of cuisine do they prefer. Managing that sheer amount of data becomes a big challenge in a digital versus a conventional means.

“The second part is leveraging that data into information. So how do I take applications that may be utilizing data, giving those applications access to the right data at the right time to be able to make the value out of it, and be able to deploy that into something that will derive ROI and capital back externally.”

What’s the largest challenge a company faces in trying to become a digital enterprise?  Driving the adoption of taking data and being able to manage it.

“The first is to examine the main legacy management mindset and management process of the enterprise and convert that into a digital world. There are years, if not decades, of processes and structures that are there in place. Converting them into a digital process flow and determining process automation is extremely difficult.

“The underlying challenge of making data into an asset rather than a cost is being able to get access to that data, to the applications, and when they are needed, on demand and to derive value out of it. One way is creating the applications and automation that will drive and lead to digitalization within an environment and being able to access the data that is behind it in order to convert it into information.

“That cannot be done across a single silo or a single application, but to be shared across applications and across users, and to derive the utmost value from those data points. This  can then lead to business value and outcomes that derive better ROI, and derive a quick and different outcome compared to your competitors.

“Many companies probably know the data is important to them from a competitive perspective.  But probably fewer have any specific strategies on what to really do with the data, and how to make it work for them.”

Without using any proprietary information or names, what are some ways that you have seen a digital enterprise really gain some actionable insights on their data?

“Discovering information on people and entities is a journey to digitalization through a transformation that’s taking place, some maybe evolving far faster than others. Companies that I have seen successfully do this have the ability to do a couple of different things.

“One is on the consumer front. They have a far better understanding of their customers, their purchasing patterns, and their spending habits.  For example, a traveler agency can discover what type of activities they like, what are the type of destinations they like to go to, and make suggestions or provide guidance proactively based on this data. Determining what is their typical spending in a particular year, and then catering services to that and being able to offer them special deals, etc., specifically to address that.  

“The same is true for a financial services company, where they are able to tell what applications are leveraging what data, and being able to give those applications more data points to leverage. That will then allow them to offer better products, whether they be specific to consumers from a lending perspective, whether they be a wealth management perspective, or whether they be a traditional banking perspective.

“In most cases, the challenge to be faced is taking data and making it actionable, where it can derive value and become information that can drive value.  You must make sure that your data on the back-end is laid out, from an infrastructure standpoint, to allow the flexibility to generate the desired business outcome.”

Many organizations have a wish list of information they would like to have about their data.  But how often do you really see any new or unexpected data, insights, or purposes.

“Once people do learn what they have access to, what is occurring in today’s digital transformation is that data comes in many forms, and data brings a variety of different value. Before an application could be tied to specific data, you could only extract the value related to that application. What you find in today’s world is those data points could have a myriad of value.

“The consumer example that I mentioned before, in terms of spending patterns, could have value for those online travel portals to provide specific destination value. But it could also have value for the card processor on the spending patterns of their customers, and that brings about a completely different value chain from the same data point.

“Identifying somebody willing to spend $1,000 on a credit card versus $100, and when  they are spending it, and then being able to customize financial solutions to those scenarios is a classic example. Taking that same example and running it through its lifecycle, where you have different use cases which may initially not be thought about, can then be extrapolated.”

“A clothing retailer may get involved in a beach-based destination. Can I sell them or can I offer them swimwear or things related to beach activity, something that earlier may not be a data point that they would even be able to think about or capture, much less derive informational value out of what would allow them a competitive advantage?”

What are three ideas are tips or keys on how to become a digital enterprise?

“I believe the transformation is something that is a journey, so an enterprise needs to make sure they have identified outcomes or results that are expected along with the milestones in that journey. That’s number one. Because if you have milestones, what ends up happening is you’re able to determine success criteria and keep moving forward.

“Second, to enable and empower digitalization requires the sharing of information across a far broader spectrum than in the past.  Making sure that you have the right security controls around data that allow people to access that data as needed, but only to those that should have access.  And the ability to move that data around so that applications can access it when they need it, where they need it, is an important component of that.

“Finally (third), I’d say infrastructure that manages the data or the underlying brick and mortar asset. All of this is necessary because facilitating data access also ties back into where the infrastructure resides, especially as digital enterprises look at a hybrid-cloud model.

“Being able to understand that, and making sure that it is structured in a manner that gives flexibility to the application in order to access data, as and when needed, becomes the final tie into this.  Strategically, ensuring that you define operational parameters that are measurable, tactically ensuring that you know you have empowerment and enablement of accessing data, and finally the ability from a technology standpoint to have an underlying infrastructure that can tie this and enable this.

“These are all three key components to help digitalization take place quicker faster in your transformation, and to be successful and responsive at any level of the data chain in the Corporation.”

How can someone really find out what it’s going to take for their operation to become data enterprise?

“One quick and easy way is to go to our website at www.datdyn.com, where we have created a survey based on customer responses. What we found is a lot of customers are asking us typical questions that allow and help them to understand where and how they can get to digitalization.

“We created the survey right on the top of the website. Take a look, and it can help guide you on the journey, and to how best to digitalize based on the survey responses, and where you’re at in the journey.”

If you are interested in moving to the cloud for storage savings and better business analytics, you can get a cost of ownership (TCO) comparison and a list of recommendations by completing a short survey on the Data Dynamics website, https://www.datadynamicsinc.com for a free assessment.

You can also subscribe to our Soundcloud channel and get access to all podcasts!