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Data Science: Breaking Down The Data Silos

by Ali kidwai•
Intel Data Center GPU codenamed Crescent Island architectural slide showcasing Xe3P AI optimized GPU IP, up to 480GB LPDDR5x memory capacity, and a 350W air-cooled PCIe form factor.
Intel’s Crescent Island GPU targets AI inference economics by prioritizing massive LPDDR5x memory capacity over costly HBM architectures within a practical 350W air-cooled design.

In today’s digitized economy, the capability to utilize data represents a real and indispensable competitive advantage. Organizations are using advanced technologies to unbolt the true value of their data. This allows them to make smart decisions, accelerate innovation, serve up better customer experiences, and respond to problems faster.

The main issue standing in the way of transforming the deluge of big data into decision-making is- Data Silos. Presently, every department has its data repository which is isolated from the rest of the organization, resulting in – many conflicting versions of the truth. Silos have made it difficult to analyze, manage, & activate data. So, here we are to discuss how you can break down the Silos and activate the power of Business.

What are Data Silos?

Data silo refers to independent sets of data within an organization. Often aligned to either IT systems or business functions, data silos are where only a limited group of people have knowledge or access to the data resources available. It is a big problem for organizations that are looking out for sheer productivity, business agility, and efficiency.

Breaking down your data silos starts with knowing how they were initially created? Eliminating data silos can help you get the right information at the right time so you can make smart decisions and save money by reducing storage costs.

Why do Data Silos occur?

Data silos occur for different reasons across various industries. Though, a common factor lies within the very structure of the organizations. Once a company is big enough, people naturally begin to split into teams to streamline work processes and take manifold benefits of skill sets.

While having autonomous departments or business units is necessary for an organization to be effective and focused, if the barriers between teams grow too sturdy, the flow of information between them slows to a trickle. And that’s when data silos begin. Typically, Data Silos happens for these reasons: –

  • Less collaborative environment
  • Company culture
  • Organizational structures
  • Loose accuracy of the isolated data

Effective ways for Breaking down Data Silos

Getting away from data silos isn’t as hard as a lot of companies think. There are numerous ways for organizations to break down data silos to make the most of it from their data. Here are the five best ways to break them down:

1. Make it a Priority- If you want to eradicate data silos at your organization, then make it a top priority. Develop a thorough plan as to how exactly you’ll eliminate it and ensure all involved employees are aware of your intentions. If possible, put together a cross-functional team to look after the consolidation process to establish smoother sailing and quicker results.

2. Promote communication and collaboration- Get rid of data silos by encouraging your employees to communicate with one another regularly. It’s also significant to embrace a company culture that celebrates the collaboration. By this you will experience better results, that will reduce the chances of data silos.

3. Company-Wide data model- Most business functions must grasp data from different parts of the organization, and, in the exclusion of an enterprise-wide data structure, they will collect data, based on their requirements, functions, and perspective. The easiest way to break down data silos is to make sure you have a data warehouse solution that has the scale and performance to brace your organization’s holistic data needs. If your intent to bust the silos, your data consumers will expect equal performance from what they have in their silo solutions today.

4. Governance- The main goal of data governance is to break down data silos in an organization. Using data governance maturity models and integrating data from all sources, organizations can holistically determine which level of governance is right for them. With proper teams, organizations can implement the policies and procedures for handling data.

5. Master Data Management– This is a core process to manage, centralize, categorize, organize, synchronize and enrich the master data according to the business rules. An efficient MDM in a central repository offers you a single authoritative view of information and eradicates inefficiencies caused by Data silos.

Conclusion

Therefore, by evolving around a plan on how to encourage employees to communicate with each other frequently, store data, and using the right tools, you can avoid data silos ”making it easy to tap into the full power of data. 

I am a proficient wordsmith encasing an experience of over 6.5 years in the field of Content Writing. Currently, I am working with Polestar Solutions. I am often praised for the ripeness to deal with immediate situations and highbrow work.I am a writer by profession and a blogger by passion. When not working in the professional vicinity, I love to document my hunch on various topics – Artificial Intelligence, Machine Learning, Business Intelligence, Supply Chain Management, Data Analytics etc. I am a dedicator and a disciplinarian. I aspire to associate with professionals and work for projects that I am skilled at, proving to be an asset to your organization/assignments/projects.“Content Adds Value”

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