Managing BI Landscapes Intelligently Using EIIG’s Similarity Analysis & Active Metadata Tools
Published On: April 13, 2023
Managing business intelligence (BI) landscapes can be a challenge across enterprises worldwide. One way to make BI landscapes easier to navigate is by using similarity analysis and active metadata tools.
As someone who has worked in business intelligence (BI) for 20+ years, and is familiar with the bloat that inevitably occurs within a BI landscape, I’ve seen first-hand how much time is saved when the right tools are in place. Bloat naturally occurs over time as new data sources are added, new ETL jobs are developed, and new reports are written. As the various environments grow, and new database/ETL/BI technologies are adopted to meet the needs of the organization, the landscape becomes increasingly difficult to manage. Many of those technologies provide 1st party utilities for determining lineage and usage, but they are usually lacking and require a lot of extra work to produce the information you need.
Orion Governance’s Enterprise Information Intelligence Graphic (EIIG) is a powerful tool for determining lineage and performing impact analysis (among many other things), which are extremely useful for maintaining the BI landscape. However, EIIG’s Similarity Analysis & Active Metadata tools take it to the next level.
Reducing Duplication and Increasing Trust
Duplication is bound to happen in any organization. Whether it’s database resources, ETL jobs, BI content, or “all of the above”, this duplication results in increased costs (for development, maintenance, and sometimes unnecessary hardware) and missed deadlines (due to time wasted on less important matters).
Duplication can also result in a loss of trust in the data since it violates the “single source of truth” principle. Reducing duplication is a good step towards saving time, reducing costs, and improving the trustworthiness of the data.
EIIG’s similarity analysis works for:
data integration environments,
and business intelligence platforms.
EIIG’s Similarity Analysis allows administrators to quickly assess the amount of duplication that exists in the landscape, drill down on the details, and act on it accordingly.
Taking Control with Usage Metrics
Reducing duplicates is a great first step, but EIIG offers more with Active Metadata – in particular, the Usage Metrics. EIIG can ingest usage data from multiple BI systems consisting of varying technologies and add value by propagating that information back to the ETL and database assets involved.
With Usage Metrics, you can correlate how users use content to the underlying jobs and tables the content is built upon. This level of insight into the BI landscape is useful for many purposes – in particular, determining which ETL and database assets are no longer used. EIIG can help identify ETL jobs that produce unused data. Eliminating unnecessary jobs will streamline development, save processing time, and help avoid missed SLAs.
Why EIIG Instead of the Other Platforms?
So why not use 1st party tools like Tableau’s Data Management or SAP BI’s Steward? These tools are useful within their own platform but cannot provide a complete view of the BI landscape like Orion’s EIIG can.
Not only does EIIG consolidate metadata from many different database/ETL/BI platforms, but it can also propagate that information across the landscape to give you a much broader view – something not possible with any 1st party or another 3rd party tool on the market today. What is more, with AI/ML-powered innovation, EIIG is highly automated and can be deployed in days/weeks rather than months/years.
EIIG is not just a BI tool – it’s much more than that. EIIG can provide value to many different roles in the IT department. However, for BI specifically, it provides a great set of features that help BI administrators manage their environments more efficiently both on-premises and in multi-cloud environments.
Eliminating waste caused by maintaining duplicates and unused content, will help save time and reduce costs. Furthermore, by helping achieve a single source of truth, users will be more confident that the data they see are correct. These benefits should be of interest to IT administrators and, most importantly, the CIO.
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