Matillion Unites Data Transformation Leaders to Discuss Data Architecture Complexities
2020 customer advisory board meeting highlights themes impacting future enterprise data transformation requirements
Matillion, the leading provider of data transformation for cloud data warehouses (CDWs), held its annual customer advisory board meeting in Q3, 2020. The virtual event brought together data and analytics leaders from manufacturing, travel, healthcare, media, and enterprise software companies, who identified several themes impacting the growing demand for data transformation tools.
Vendor selection and standardization of solutions for data management and integration pose challenges.
Businesses share concern over the number of different vendors as the need for consistent data governance and business logic makes it challenging to settle on solutions because of varying standards. There is widespread desire to replace or consolidate certain technologies, and a need for increased capabilities within current solutions that could reduce the number of disparate products used for data integration. Additionally, there is a preference for more technical integration across different solutions for data management.
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New methods of data collection introduce data quality management complexity.
Enterprises invest heavily in adapting data/metadata and continually strive to increase data quality. Some companies have older, legacy ETL systems that cannot leverage new data sources like IoT or real-time data streaming. Companies want to be able to stream operating data at millisecond values and glean value from the data. This is especially valuable for businesses in service industries that use real-time data to monitor performance. They also want to enable their customers to access data analytics from a smartphone, from any place at any time. However, these goals are difficult for companies to achieve because of the data governance and data quality implications of accessing data quickly.
Lack of a data-driven culture inhibits action with data.
Enterprises are experiencing challenges implementing metadata – not only with tools, but with culture and process. Metadata automation is desired to help non-technical users understand how to use data to make decisions. Without this, it is difficult for businesses to be truly data-driven outside of IT.
Companies are struggling to align managers with decades of experience, who assign more value to hardware and other tangibles, with younger managers who require different business models, and are driven by making money from data. There is also a need to better support data scientists within the business. This requires equal digital citizenship, enabling all workers with the ability to visualize data and use it to create solutions.
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Enterprises must support data-savvy business users and self-service.
Democratization is a force within enterprises who want to lessen a dependence on IT and greatly improve efficiency. Enterprises with savvy business analysts can go directly to the data, eliminating IT as a bottleneck. The even bigger benefit is that while they are accessing data themselves, they often find other ways to leverage data that they did not know existed before.
Many businesses need to create a powerful data governance policy that satisfies compliance and still allows everyone in a business access to the data they need. Clearly seeing where data is coming from, what it means, and how it was calculated, is of critical importance. The plethora of data makes this more difficult, while also making it easier to read the wrong data.
“Data lineage is important. Users want to know why a data set did not get to them, why it is out of date, why a specific row didn’t get through,” said Edward Scura, senior program manager commercial data & platform, Novartis. “They need the history of hops and jumps. Our business users are very technical, very savvy. This is the least we can do to make them productive.”
“Our latest customer roundtable event illuminated the ongoing complexities enterprises deal with now and in the future, while allowing idea-sharing among talented enterprise data leaders,” said Matthew Scullion, CEO of Matillion. “The need to harness and extrapolate data from ever-increasing data sources, along with the need to deliver valuable insights in real-time to both employees and customers remains. We value our role working in partnership with the forward-thinking organizations we serve to glean business value from their data.”