When we look at data and how the requirements for integration have escalated, it all comes down to the data environment. What is the process? Where does it end up? The real question is, how is it being managed and what method or solution works best for each user or organisation?

A new way of integrating data is to ‘bring it home’ by simply extracting and transforming it.

It’s not a new idea to draw on data when making strategic decisions – businesses have been doing so in one way or another for a long time. But in recent years new technologies, coupled with an increase in the amount of data at our disposal, have brought about the emergence of the data-driven organisation: businesses in which every decision and process is anchored in data.

Analytics has been a key focus area of Internal Audit for many years, but this has not brought about a fundamental change in the way the overall process is conducted.

While many organisations include core analytics, data skills and toolsets, the outcomes of analytics testing are not optimally integrated into their Internal Audit processes. Internal Audit teams that leverage traditional analytics are reliant on IT support, and have to copy or move data from one location to another before they are able to use it.

A retail bank approached Intenda to conduct a Fraxses point solution. The bank’s data management systems did not provide a comprehensive customer view. As a result, client managers were unable to generate reports promptly. The point solution’s objective was to deliver a 360° customer view, thus enabling client managers to provide up-to-the-minute reports on demand.

An energy provider contracted a professional services consultancy to investigate the factors driving the customer churn it was experiencing.

Recognizing the Fraxses data platform as the ideal solution to identify statistical correlation for churn across recorded data events, the consultancy elected to undertake the investigation in partnership with Intenda.

According to Gartner Top Trends in Data and Analytics for 2021, “Data integration and data preparation are among the top three technologies that organizations would like to automate by the end of 2022.

A data fabric’s architecture addresses the challenges that constrain the monolithic approach, and simplifies data integration and management.

The importance of master data cannot be denied. There are a variety of articles, books, and events that emphasize its importance. Yet for many organizations’, it is a struggle to organize their master data in such a way that it can be used by many data consumers.

Those who have been able to organize it well, use master data primarily within a limited and controlled set of applications.

COVID-19 has had an unprecedented impact on individuals, healthcare systems and economies worldwide.

The data mesh is a new approach
to designing and developing data
architectures.

It is no longer special for organizations to own multiple really big data systems.

You can buy an ETL tool, a reporting tool, and a database server, but you can’t typically buy a data fabric.

A whitepaper focusing on aspects of data virtualization that need attention with benefits explained by one of the most influential BI analysts in the world.