Data Black Holes: Are data silos undermining digital transformation?
BARC surveyed participants from around the world to learn what data intelligent companies are doing to overcome their data silos. Below are some of the recommendations:
- Create transparency around decentralized data processes
- Make digital transformation a primary business initiative for the entire organization
- Plan a logical architecture that ensures combinability of physically distributed data
- Implement a common data language in order to make data accessible across the organization
Read this BARC report to learn more about the challenges that organizations face with data silos and the ways in which organizations can overcome their existing black holes.
We are in the age of digitization where large amounts of data are being created and used everyday. But with this proliferation of data, organizations struggle to find and access this data, causing data silos across the organization
The existence of data silos is nothing new. Data-producing applications were once isolated systems. They were built to at least partially automate a specific subtask of a business process. The transactional data was stored in isolated data sets and initially served only one purpose, namely, to document the transaction that had taken place. Over time, enterprises realized that data is worth more.
Utilization of operational data for enterprise management helps to gain insights into the current state of the business and supports fact-based decision-making. This has been important for decades. However, the operational data stored in data silos was not suitable for this task. Many companies, therefore, built a data warehouse to consolidate their operational data silos.
In the age of digitalization, more extensive data and analytics requirements have emerged for which the data warehouse was not sufficiently designed. Data-based insights are being used to automate decisions. The goal is to make business processes faster, more efficient and less vulnerable to risk.