Real-time Data warehousing: Logics into learning

Deep into the modern era, data is way past the concept of being just an ‘entity’. It is central to major business processes and current technology stack highly favors the idea of a world managed by data-driven insights. ‘Using data of the past to correct the possibility of future’, the prevalent idea might still be in its infancy, but its true potential holds immense possibilities for the upcoming.

It is evident that enterprises are already excelling in big data applications and driving-in crucial business insights through business intelligence tools. Data analytics is extensively being used to make accurate business decisions and procure greater benefits with same resource pool. With an estimated volume of 2.5 quintillion bytes of data being generated every day, improving data management techniques becomes more crucial than ever.

For a long time, traditional warehouses were used to store data that could later be extracted as per user requirement. Data warehouses are nothing but a relational repository where an organization stores data collected through various operations. Data is refined and selectively stored to further aid organization’s decision support systems and crucial analytics. Unlike most of the technologies surrounding data management, data warehousing has least evolved. But with the emergence of business intelligence and predictive analytics, conventional data management concepts have largely transformed. Digital storage space has evolved for the common good, ETL (Extract, Transform, Load) and data centralization are now quaint, making way for a smart storage environment where data is directly accessed and assessed at its very origin. Data management has turned ‘intelligent’ by fostering end to end logical storage systems, often tagged as virtual data warehouses in the tech market.

Cloud technologies have largely facilitated the advent of Logical Data warehouse (LDW) across major industry verticals, allowing the enterprises to extract better outcomes without any additional investment or application. Modernized data warehouses are remodeled to uphold the growing data variable, accounting to the advancement in enabling technologies like real-time data virtualization and multi-dimensional data processing. With LDWs enterprises can reimage their storage solutions with near ‘Zero latency’, mapped over a revolutionary server-less storage system, which can potentially change present day equations by out-focusing transactional processing and heavy data inconsistency.

Pratham software excels in enterprise level data analysis and BI services, specifically devised to help organizations extract the most out of their business process. Our business solutions empower the core operational and functional abilities so that our clients can reach out to the best of their potential and earn up-surged business revenues.