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Data Federation – Essential to Modern Data Management Strategy

Bandev Ghosh

@Bandev

October 31, 2022

Data Science & AI Community

279

With business decision-making becoming more data-driven, data management strategies are also undergoing refinement. Businesses that are sitting on large volumes of data have a need to quickly view, access and query relevant information. However, there are significant challenges resulting from the type and format of data, data location, control of databases, data quality and accuracy. There arises a need to set up data integration techniques to ensure overall visibility while making crucial business decisions.

Data is generally siloed across departments with no single-source-of-truth available. This hinders decision-making and running operations effectively. Additionally, data volume is not static, it is increasing by the day. There are different data types, structured, unstructured, text data, image data. As data volumes grow so do the silos within them.

What is Data Federation?

Data Federation is a software process that allows multiple databases to function as one. It provides a single data source to front-end applications, taking data from a range of sources and converting them into a common model. Data Federation is closely related to Data Virtualization framework. While they are related, the latter has a broader approach in terms of extra features, applications, and functionalities.

Data Federation supports the exploitation of multiple disparate data sources and can also be termed as data fusion solutions. It is a design philosophy and a modern data architecture pattern. Federated data architecture is the next-gen approach to sophisticated data integration.

How does it serve modern day data challenges?

Managing data effectively is one of the key challenges facing businesses. There are multiple sources of data, which lack of coherence, suffer from dissimilarity in format.

Data Federation has become a crucial part of Data Management and virtualization strategy. While virtualization is a wider concept which includes applications, dashboards etc., Data Federation helps to consolidate data from disparate sources and instead of creating another copy of the data, stores it on a virtual database, enabling virtual integration. It combines cloud, data warehouse, data integration etc. Data Federation takes information and data from various sources and converts into a single format bringing uniformity and a single pane view.

Federated Data stays in the store where it belongs while making it available to data consumers across the enterprise. One of the key benefits of Data Federation is that it allows for real-time access to information and data.

source: www.tibco.com

Benefits of Data Federation:

Provides seamless access to heterogenous data: Provides visibility in to stored data across the enterprise without having to access each individually. It enables data consumers to run queries. It helps to bring information from disparate systems together better than legacy processes such as ETL

Single source of truth: With the proliferation of data types and storage systems – both legacy (SCM, ERP, CRM) as well as cloud-based systems there can be issues related to trustworthiness of the data. Data silos prevent users from accessing the requisite data, particularly if it is widely spread across the enterprise. Data Federation is a modern and holistic approach to eliminating data silos and enabling easier sharing among users of data.

Lends reliability to AI/ML workloads: Reduces the workload of Data Scientists in terms of data accuracy, consistency and by removing outliers. A large part of this can also be automated thus making data ready for training and building algorithms.

Does not need heavy coding experience: In the modern low-code era, Data Federation can be achieved without significant barriers. The runtime software can be installed on a regular server and the queries can be run.

Data Management can be challenging when data is scattered across the enterprise. Data Federation has emerged as a key element of modern data management strategy. Federated systems allow for better integration of data eliminating the need for additional data storage systems. It brings together data from multiple sources on to a single plane. Advanced analytics and ML workloads need seamless access to clean data in a uniform format that can be processed quickly for real-time and improved customer interactions. Data Federation, as a subset of Data Virtualization, is likely to remain a key solution for Data Management strategies.

#AI #AI #artificialintelligence #machinelearning #AI #datascience data management

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Bandev Ghosh

Senior Manager