Consolidating data warehouses

This would require a lot of planning and architecture as typically; the banks are a conglomerate of many entities operating entirely independently at times and often crossing the geographical boundaries.There are thousands of repositories where the data needs to be acquired and standardized in a format that it could be leveraged to obtain meaningful insights.However, to gain a point-in-time visibility and understand the high-level operational aspects of any business, the historical data plays a vital role.

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Based on the normalization concepts, this architecture was introduced by Bill Inmon in late 70s.

In a 3NF data warehouse model, various entities are normalized to remove redundancies and then joined together if the data is required across those entities.

To enable enterprises to more easily take advantage of the benefits of a cloud data warehouse, Attunity provides technology for managing real-time data warehousing, automating data warehouse processes and testing data warehouse implementations.

Attunity enables universal data availability by replicating, synchronizing, consolidating and ingesting data across all major data warehouse solutions.

As the data in the transactional systems would get purged periodically, it would not be the case in these analytical repositories as their purpose was to store as much data as possible, hence the word “data warehouse” came into existence because these repositories would become a warehouse for the data.

Data Warehousing as a practice became very prominent during late 80s when the enterprises started building decision support systems that were mainly responsible to support reporting.historically however, that is just one form of a data warehouse.A data warehouse can be centralized or distributed or a logical construct of many physical data warehouses altogether. The process of consolidating data and analyzing it to obtain some insights has been around for centuries, but we just recently began referring to this as data warehousing.With Attunity, organizations can derive more value and insight from their data warehouse environment, improving agile analytics while minimizing cost and effort.In a previous CTA, we discussed building a 360-degree view by stitching together data from a la carte tools such as Google Analytics, Facebook Pixel, and Salesforce.Data Vault modeling is based on grouping the entities based on their propensity of changing over time in form of hub, link and satellite. Hubs contain business keys along with other key source fields that typically do not change ever.