The market trend that we are seeing with our customers is a desire to operationalize these data assets for the benefit of other enterprise integration and analytics initiatives.
In a previous blog, I wrote about the convergence of modern BI with traditional BI in customer-facing analytics initiatives. On the data front, we are seeing a similar convergence between self-service data prep driven by the business and enterprise data integration and integrity being driven by IT.
A number of data-savvy personas (data engineers, data stewards, analysts) tied to strategic business units of an organization are using our self-service data prep solution to prepare data for analytical purposes. It could be to support data science initiatives or support downstream visualization and insight discovery. The benefit of this approach is a more agile and collaborative experience driven by people who have the best understanding of the businesses data. The value of this approach is driving the next market disruption: augmented intelligence, which uses AI and machine learning algorithms to analyze vastly greater amounts of data and find the relevant trends, patterns, clusters, and outliers in your data. What this approach lacks is governance, data integrity, and security. These data assets produced by the business drive great value, but they are not “curated” for use in operational applications.
The market trend that we are seeing with our customers is a desire to operationalize these data assets for the benefit of other enterprise integration and analytics initiatives. Information Builders has long had a leadership position in data management, providing deep capabilities in the areas of enterprise data integration and integrity. Our products form the foundation of our ability to add governance, quality, mastering, and “trust” to these data assets.
What is most interesting in this equation is the equally important market trend traveling in the opposite direction (IT > business) that we are poised to capitalize on. The insight that a business-centric data persona can identify is limited by the amount of data (enterprise, unstructured, 3rd party, etc.) that they can consume and make sense of. Traditionally, access to enterprise data assets has been limited to users of self-service data prep or visualization tools. This is where a data catalog comes into play.
A data catalog manages the information supply chain of an organization. It provides curated data assets to the business in the same place that the user-created data flows are managed. It contains the best of both worlds: data governance and trust in the curated data assets, and a managed and collaborative experience around the “un-curated” data assets. Popular capabilities allow people to collaborate on data flows, rate, discuss and add business terminology to help data understanding. Not surprisingly, this provides the ideal environment to operationalize highly rated, high value data assets that originated from the business.
How can we capitalize on both of these market trends?
Quite simply, our integrated platform offers self-service data prep and enterprise data management capabilities. Paired with our highly scalable analytics platform and data science “at scale” offering, we find this combination to be a formidable offering in competitive evaluations.