Operational Data Stores (ODSs) aren’t an entirely new concept – they were first introduced in the 1990s. However, IT teams are starting to take a fresh look at Operational Data Stores as a central part of their data strategies. An ODS is a welcome addition to an organization since it integrates disparate data from multiple sources for reporting, while insulating operational information systems from reporting demands and system overhead. This approach eliminates batch processing, is more flexible, and delivers faster results in support of timely reporting and analytics - high priority in order to make timely, well-informed business decisions.
In many organizations the IT ecosystem is highly complex, with various software systems supporting different parts of the business. Bringing many types of data from a myriad of source systems and unifying it into an ODS for reporting and analytics can be a major undertaking. The process often involves significant time, effort and cost. Equally challenging is selling the approach to internal influencers and stakeholder such as application owners, real-time BI administrators, ETL developers, data scientists, and the CEO. However, The ODS is essential as a gateway between legacy production systems and an Enterprise Data Warehouse.
Ad hoc sharing approach:
An ODS, in combination with Qlik Replicate®, solves the above-mentioned challenges and makes real-time operational data available across the enterprise.
A high-performance, easy-to-use solution, Qlik Replicate can automate the creation and management of an ODS. Qlik Replicate supports homogeneous and heterogeneous source environments, and provides organizations with a way to expose siloed production systems in a cost-effective way. Using Qlik Replicate for ODS, organizations can achieve faster time-to-value for Big Data projects and deliver a more complete and trusted view of the business. As a result, companies can harness the power of Big Data to drive new insights and deliver competitive advantage.