Data Federation: Why is it important?

Businesses manage a wide variety of data to run their operations effectively. They collect and store different data types, such as big data, and structured or unstructured data. As businesses grow, the size of their data store grows, and so do the silos within them. In large organizations, data is often siloed across departments, making it tricky to get overall visibility while making crucial business decisions. Data federation eliminates this hassle and allows you to access all data from a single location. Many businesses implement data federation through virtualization software to gain seamless access to their distributed heterogeneous data.

What is a Data Federation?

Data federation is a data management strategy that can help you improve data quality as well as data accessibility. Data federation is the process of querying data from different sources into a single virtual format.

These federated systems allow for better data integration and analytics than other types of databases because they eliminate the need for massive data storage systems and can provide more accurate information by aligning data across multiple sources. If you’re considering using a federated data model for your business there are a few things you should know.

Why is it so important?

Data federation is one of the most critical data management strategies in today’s data-driven world. With so much data being generated and collected every minute, it’s necessary to have a way to manage all of this information right when you need it.

Businesses across many industries are using data federation for better search results and analytics as well as improved customer interactions. Customers expect companies to be able to provide them with relevant information that pertains specifically to their interests or preferences; businesses can do just that by connecting different sources into one system where they can then use data integration techniques such as de-identification, masking, and anonymization effectively and efficiently. In a federated data model, all of this can be done without creating and storing redundant copies of data.

Data federation helps solve many of the problems that businesses and organizations face when it comes to raw data, whether it has to do with large amounts of data that need storage or a lack of consistency among the data.

Benefits of data federation

With the growing focus of organizations on creating an easy-to-use data accessibility solution and eliminating data silos, data federation has gained popularity in the past decade.

Data federation offers multiple advantages for organizations, including:

• No additional storage requirement: Data federation software doesn’t copy data from individual databases to any repository. Since data integration is carried out virtually, you don’t need to allocate separate storage space or hardware.
• Faster access to data: Data federation offers a single source to access any data. It eliminates the hassle of making queries in individual databases to get what you need by providing a single platform, enabling you to access data seamlessly and save time.
• Ease of use: Data federation tools don’t require you to possess knowledge of different coding languages. You need minimal coding knowledge to make queries and access the data.
• Cheaper option with minimum risk: Since data federation doesn’t create a separate copy of data, it prevents you from spending on costly storage hardware. At the same time, it minimizes the risk of data loss as there is no physical data movement.
• Makes data scientist’s role easier: Data federation takes care of cleansing data, making it easier for data scientists to use accurate and consistent data and collect insights from it.

Data Federation in Business

One of the biggest challenges facing businesses today is managing data effectively. There can be multiple problems with data:

• Multiple cloud databases and different sites restrict access
• Large volumes of data need massive storage
• No consistency among data, requiring effort and time to cleanse and organize
• No single format of how or where data is stored

Data federation takes away a lot of the problems associated with raw data, saving businesses time and money. For instance, a data federation converts information from multiple sources and combines it into a single format. Then, it places all the databases in a single store virtually. This means, that rather than creating another copy of the data, it integrates virtually, eliminating the need for another storage system.

Data federation should be part of a data management and virtualization strategy. This strategy combines cloud systems, data warehouse extensions, data integration, and a host of other data management strategies.

Conclusion

Data management can be challenging, especially when data is scattered across multiple systems that all need to work together. However, federated data models can help simplify data management, and when used correctly, can save businesses time and money. Data storage is extremely costly. Eliminating the need for redundant data copies through a federated data approach is an effective way to reduce data storage costs.