Propelling the Data-Driven Enterprise by Building a Single Source of Truth across Enterprise

As businesses expand, there are multiple challenges that the existing enterprise data warehouses begin to experience. Storing and synthesizing of large volumes of data are among the key challenges faced. Legacy enterprise data lake lacks the flexibility and scalability required to make accurate and timely business decisions.  A single source of truth is the answer to these challenges. Building a unified data model helps an organization to create a holistic view of their data that can be utilized across the enterprise with ease and confidence.

Single Source of Truth across the Enterprise: Things To Consider

A single source of truth is an end-to-end solution that helps convert your existing data silos to modern data architecture or an on-premise big data warehouse. The solution follows an incremental approach and comprises of five stages – assessment, transformation, preparation, access, and consumption. Each of these stages drives immediate business benefits and offers a measurable return on investment. The risk of manual errors and the time involved can be easily reduced using an automated transformation. Creating a single source of truth isn’t an easy task and requires considerable investment in terms of money and time.

The key success factors for building a single source of truth across an enterprise are mentioned below:

Strong Central Mandate:

This includes changing the way an organization stores, collects, and uses data. Getting a senior management sponsorship is the first step involved in the process. It is important to communicate the importance of this exercise and the type of business value that can be derived from it. They should be able to trust the initiative and be willing to invest in processes, people, and technologies that help build a data-driven business.

Choosing the Right Technology and Platforms:

There are numerous tools and technologies available for data-related projects all serving a specific purpose. The successful organizations assess their needs and choose platforms that are best suited for them.  They leverage big data and technologies to consolidate their data silos to meet the analytical needs of their business users. Blending data in from silos is a time-consuming task and the risk of errors is also high. Therefore, making use of technologies to automate the process greatly helps.  By choosing the right platform and technology, current goals can be achieved that, in turn, prepares the organization for the future.

Focusing On Results:

For building a data-driven decision-making process data must be made available across the organization in a consumable format. Instead of making the data accessible to a few, it must be made available to all. This results in better decision making within the organization. This can be achieved by building a BI consumption layer on top of the data platform. Enabling self-service access to data makes it easier to utilize it for profitability.