• Sanjay Rajashekar

Wipe out the Data Silos at the EDGE





“Stay away from the daunting data silos at the edge by leveraging Unified Data Management”


At times we have to trust our intuitions and the gut feeling to make decisions in our life. But we can not go by intuition all the time especially when the decision can impact many.


In an enterprise like manufacturing, petroleum, or any industry that comprises several business units and Line of Business groups, every single decision matters. It has to go by the “Data” rather than assumptions as it may turn into a catastrophe.


“Data from the Edge IoT Devices” are indeed a valuable asset of the facilities team.


But at the same time, what if the data volume is massive and the way in which it is interpreted is different from application to application?


Ain’t it sound dreadful?


It complicates any decision-makers who are responsible to take critical decisions for the organization.


And the Enterprise Edge is becoming critical as millions of IP enabled IoT devices are coming into the foray and data they generate about the environment is extremely rich but is highly fragmented due to point solutions. The Line of Business teams or OT teams are grappling collecting all this information from fragmented solutions.


We understand your plight and let’s see how we can alleviate this effectively.

What are the “Data Silos at Edge”?


An enterprise edge has millions of IoT devices and is cleaved into multiple sections or Line of Business groups / OT Teams.


As we all know, to unravel the maintenance, robustness, efficiency, and security of the operations and for various reasons, the facilities team procures IoT devices from diverse vendors.


Each OEM comes with its own firmware and software amenities to stay abreast in the competition.


These apps acquire, transfer, analyze, and interpret the data in their own terms. This differs from software to software.


The facilities team utilizes these data from multiple sources to control the edge environment and ensure security.


These diverse data with restricted access segregated from each other are called “Data Silos”.


And as time passes by it grows further.


What are the reasons for data silos at the edge?


Data silos evolve for various reasons like,


1. Booming Organisation

Any firm whether it is a startup or a huge enterprise, its vision would be to scale up its business to the next level.


“The journey towards growth is not a walk in the park”


As the business boom, it is important to

  • Expand the infrastructure

  • Reduce the vulnerabilities

  • Update the policies and procedures

  • Tighten security processes

  • etc.


Data acquisition, data governance, data storage, and transfer processes which were simpler before become tougher. We cannot change everything overnight and most of the time it is done on demand.


Each Line of business Team / OT team follows its own guidelines and handles data accordingly. Until pain starts impacting the business most of the time it is left unaddressed. This grows into havoc.


Suggested reading: 5 Tips for building a solid IT Infrastructure



2. Multiple Applications





For enterprise efficiency and for many other reasons we rely on multiple third-party edge device apps and tools.


The boon of SaaS, PaaS, cloud-based apps facilitates the enterprises to avail of one within a short span.


But the roadblock here is, they never befriend each other on a click. The data transfer between these tools or apps is not effortless.


When there is a need for productive exchange, it’s hard to go back to the roots to alter the processes. We may have to sacrifice various other data in the deep dive and leave us in a chaotic situation.


3. Change in Facilities Team


Enterprises are known for their distinct and clear administration. When a team member at the facilities team leaves the enterprise, it is his responsibility to handover the operations carefully to the next promising personnel.


This is a common practice prevailing in any organization. Unfortunately, this is not the case most of the time.


In order to speed up the relieving processes, the facilities personnel finish his customary documentation and leave as early as possible.


Edge security needs clear documentation of each device and sensors deployed in the enterprise. This can facilitate the next person with a reference point in times of trouble.


When this is not the case, undoubtedly the new employee is in trouble.


He/she realizes this mess only when serious anomalies are detected.


If you have nodded to any of the above, then alert! You are about to land in a commotion.


How can we resolve this? - Unified Data Management for an Enterprise Edge makes this happen.


What is Unified Data Management for the Enterprise Edge?


When the data from diverse applications are integrated and accessed from a common repository, it is Unified Data Management.


Cloud accompanies the process and builds an enterprise-wide framework that simplifies the data governance process.


It results in enormous benefits.


What are the benefits of Unified Data Management for the Enterprise Edge?


1. Faster Decision Making


“Managers at a typical Fortune 500 company may waste more than 500,000 days a year on ineffective decision making”

-Mckinsey


It expedites the decision-making process in the organization. When there is a new market challenge or if we are put into an unprecedented challenge, we always go back to our records to gather all the information.


We analyze how we reacted to those scenarios and how we had overcome the same. These references help us to speed up our decision-making process and we involve in the process with more confidence as there is proof.


Example: When a node at a particular department is hacked multiple times, we check the previous records to know about its vulnerability and the security patches done


The quality of these data-driven decisions is high and they seldom fail.


Suggested reading: 3 keys to faster and better decisions


2. Unifies the OT Teams

This indeed fortifies the relationship between the departments in an enterprise.


When all the Line of Business & OT teams transfer and access the data from the same centralized repository, it facilitates transparency between them.


Whenever a critical decision is taken, it is not biased as it derives data from each section.


Data is now not solely under the control of data admins. Business decision-makers, technical teams, sales and marketing teams, Information security teams all handle the data from the same repository.


Moreover, each information is brought in front of the business decision-maker that conveys what hinders efficiency and productivity.


3. Higher transparency

This indeed enhances the transparency in the edge environment.


When all the applications transfer and access the data from the same centralized repository, it facilitates transparency between them.


So the facilities personnel doesn’t have to hover over multiple apps to understand the device’s health.


Whenever a critical decision is taken, it is accurate as it derives data from each application.


Moreover, each information is brought in front of the business decision-maker that conveys what hinders efficiency and productivity.


4. Wallet-Friendly

Unified Data Management for an enterprise edge provides us various valuable in-depth insights. Not a single critical piece of information is missed.


All the structured and unstructured data are now interpreted and following a unified pattern. This helps us not only to understand the functioning of the edge environment but also saves the wallet of the business owner.


The Sooner the vulnerabilities are detected, the faster are the rectification procedures.


Doesn’t all these sound productive? But will it take a lot of effort, time, and money for implementation?


Not really.


Smarthub.ai’s INFERPlatform - Unify all the data at the Enterprise Edge


Our INFER data lake can infuse data from all the different platforms in your organization into a single platform for data governance.


Further, we leverage the power of Artificial Intelligence and Machine learning to accompany proactive decision making.


Apart from being the common reference point, AI/ML utilizes the data repository to predict future failures. As this was done manually before, we have to invest a lot of our time, allocate a resource to take necessary actions. And it is also of less accuracy.


Smarthub.ai helps you to wipe out these impediments effectively and allies you to take critical business decisions with the power of data.


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