Steve, the Head of Business Intelligence at a leading insurance company, pushed back in his office chair and stood up, waving his fists at the screen. “Why aren’t the numbers in these reports matching up? We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” In a panic, he went from desk to desk asking his teammates if they had been working on the same reports that day. Maybe they had switched one of the fields?
The analysts and architects on his team wouldn’t be able to help him much even if they had touched one of the reports. They deal with tens if not hundreds of reports each day…
In order to figure out why the numbers in the two reports didn’t match, Steve needed to understand everything about the data that made up those reports – when the report was created, who created it, any changes made to it, which system it was created in, etc.
Steve needed a robust and automated metadata management solution as part of his organization’s data governance strategy.
Enterprise data governance
Enterprises, such as Steve’s company, understand that they need a proper data governance strategy in place to successfully manage all the data they process. This is especially when there are multiple BI databases, ETL, and analysis tools involved. To avoid situations like Steve’s, enterprises must be able to ensure that the entire lifecycle of their organization’s data is high quality. In essence, they need someone (or something) to come in and enact order.
Data governance is hugely important for enterprises needing to know their data inside and out. Data governance tools are available to help ensure availability, usability, consistency, data integrity and data security. This helps establish clear processes for effective data management throughout the enterprise. Enterprise data governance tools also work to prevent the adverse effects of poor data quality and aim to ensure that the entire enterprise can actually use its data. Data governance provides all data management practices with the necessary foundation, strategy, and structure needed to ensure that data is managed as an asset and transformed into meaningful insights.
Metadata in data governance
What many enterprises have not yet come to terms with when implementing their data governance strategy and supporting tools, is the criticality of metadata in the process. Metadata is essentially the ‘data about data.’ It provides the value and purpose of the data content, thereby becoming an extremely effective tool for quickly locating information – a necessity for BI groups dealing with analytics and business user reporting.
According to Donna Burbank from Dataversity, “metadata helps both IT and business users understand the data they are working with. Without metadata, the organization is at risk of making decisions based on the wrong data.”
Having a metadata management system in place can greatly streamline and enhance the collection, integration and analysis processes across multiple data sources. Without it, enterprises are poised to forfeit the deep insights that big data can offer. Metadata allows organizations to manage the entire data life cycle, processes, procedures and customers or users affecting specific business information. Metadata can also provide an audit trail that can be essential at any given point in time. Therefore, metadata governance is the foundation for harnessing these vast amounts of data from new disparate data sources and information repositories before they become unmanageable.
Many data governance tools out there today simply don’t include metadata management as part of their holistic offering, and if they do, the metadata management tool often requires manual installation or onboarding that could take time-crunched enterprises months to set up.
Metadata Management is a Strategic Data Imperative
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Automated metadata governance
More and more enterprises today are realizing the dire importance of a metadata-driven approach and with that, a management program to support structured data and big data for BI. They know all too well the issues that plague BI teams with regard to data consistency, better understanding data relationships, reporting accuracy, operations, data cleansing, building new processes. Enterprises fully understand the critical value to the firm. These enterprises are especially intrigued by Octopai’s solution that automates the entire metadata management process, enabling organizations to quickly locate and fully understand their data in just seconds.
This is especially important when it comes to PII, or personally identifiable information. Data governance solutions for data compliance examine all elements of the metadata which helps solve this issue. Every new data source and any alterations to existing data sources are instantly classified so nothing falls through the cracks. Data that looks to contain PII will be flagged for additional review by the data governance team. Throughout the world, governments are passing laws that define who is the true owner of the data. Basically, all data that comes into your (or your company’s) possession is not yours to do as you please.
In order to understand the full picture of your data and see exactly where the data came from, look to automated data discovery and data lineage solutions, such as Octopai, that will enable your BI & Analytics team to see a detailed visual map of the entire data landscape so that you can easily find and understand data scattered throughout multiple systems in the environment.
The data journey governed
Once Steve’s team decided to include Octopai in their data governance program, encountering mismatched reports became a non-issue. The BI group can quickly locate where and why specific mistakes were made, and easily correct them, by utilizing automatic discovery and data lineage.
Steve feels a renewed sense of confidence with Octopai at his fingertips because he can track the entire data journey and know everything there is to know about the data in the organization. From automatic discovery to forward and reverse lineage, automated metadata management is an absolutely critical component of data governance, and ensures better control and management of data to enable business strategy, improve business outcomes and reduce risk.
Enterprises today are putting data governance at the top of their agendas, but until they incorporate an automated solution for metadata management, their governance strategy will continue to shake their fists at the computer like Steve.