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 played with 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 touch 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 today understand that they need a proper data governance strategy in place to successfully manage all the data they process – especially when there are multiple BI databases, ETL and analysis tools involved. To avoid situations like Steve’s, enterprises much be able to ensure the entire lifecycle of their organization’s data is high quality. In essence, they need someone 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, to establishing processes for effective data management throughout the enterprise. Enterprise data governance tools also strive to prevent the adverse effects of poor data quality and aim to ensure that the entire enterprise can actually use its data. On a whole, 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 information.
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. As the ‘data about data,’ metadata provides the value and purpose of the data content, thereby becoming an extremely effective tool for quickly locating information – a must for BI groups dealing with analytics and business user reporting.
Having a metadata management system in place can greatly streamline and enhance the collection, integration and analysis processes across multiple data sources, and without it, enterprises are poised to forfeit the deep insights that big data can offer. Through metadata organizations can manage the entire data life cycle, processes, procedures and customers or users affecting specific business information, and can 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 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.
Automated metadata governance
More and more enterprises today are realizing the burning importance of a metadata-driven approach and management program to support structured data and big data for BI. They know all too well the painpoints BI groups are suffering from with regard to data consistency, better understanding data relationships, reporting accuracy, operations, data cleansing, building new processes etc. and 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 understand everything about their data in seconds.
Data discovery and data lineage solutions, such as Octopai, work automatically to easily and quickly map out an organization’s entire BI landscape, providing complete data lineage with a detailed visual map to show the BI team where each calculation was made in each system leading up to the current report. With this easily accessible information, changes can be implemented accurately, in a fraction of the time.
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 be handicapped.