According to Statista, global data creation is expected to surpass 180 zettabytes by 2025. It’s become increasingly necessary for organizations to effectively process this abundance of data. So the question then becomes: what is unified data and why is it important in an increasingly data-driven world? Simply put, data unification is merging fragmented data sources into a single, unified view. In this blog, we’re going to give you an overview of data unification and how it can be used to boost cross-team results.
What is Unified Data?
The Negative Impacts of Siloed Data
In today’s data-driven world, businesses and organizations rely heavily on data to make informed decisions. However, when data is inaccessible to other departments or teams, it can have several negative impacts. Below are some of the many downsides to siloed data that you should be aware of. Understanding these consequences can help you guide your team towards a more productive solution to data storage in unified data.
Data siloes influence company culture, and not sharing data causes teams to function independently rather than collectively. Working together can be more effective when processing data. If departments don’t collaborate, then they feel like they must work on their own, which in turn creates a reluctance to share data, continuing this destructive cycle.
The Benefits of Unified Data
Steps to Implement Unified Data
Data unification can be a daunting task, but with a structured approach, organizations can successfully unify their data and reap the benefits. Here are some steps that organizations should consider when implementing unified data.
Understand the Current Data Landscape
This involves identifying where your data is currently stored, what data exists, how it’s gathered, and who is responsible for it. Understanding the current state of data can help organizations identify potential roadblocks and plan a roadmap for unifying data.
Establish Data Governance
This involves creating policies and procedures for data management, such as data quality standards, data security protocols, and data privacy policies. It is important to have a data governance framework in place to ensure that data is managed consistently across the organization.
Implement a Data Management Platform
This involves selecting a platform that can integrate with various data sources and provide a single source of truth. A data management platform can also provide data cleaning and transformation capabilities, which can help organizations ensure that data is accurate and consistent.