The demand to become a data-driven business with a competitive edge in the digital economy is greater now than ever. BI and analytics is recognized as the cornerstone to success today.
As the value of data becomes better appreciated, organizations are deploying a multi-pronged approach that includes making data access and insights available to a broader swath of users as opposed to it remaining limited to small groups of analysts or executives, offering compelling data visualizations, and making data available more quickly for decision making.
The key, many believe, is creating a data architecture that helps enterprises get the greatest benefit from their data with a focus on allowing end users to introduce and prepare new data sources.
According to Big Data Quarterly columnist Lindy Ryan, there is essentially a “data revolution happening across the globe.” While using visualization to tell stories about data is by no means new, she notes, they are now being told in more influential and impactful ways than ever before. Meanwhile, charts and graphs created 5 years ago are far different than the visuals now being produced with best-of-breed tools.
In addition to broader data access and better visual representation, speed in analytics is also a critical concern. The ability for enterprises and decision makers to analyze data from an array of sources, both internal and external is more important than ever in order to sense and respond to events that may have a critical impact on markets, customers, employees, facilities, and internal operations—be it a customer clicking on a retail website, a banking system detecting anomalous behavior, or a machine sensor sending an alert for maintenance.
In fact, “speed to value” is the new metric that companies care about, and data is a key differentiator, noted Joe Caserta, founder and president, Caserta at Data Summit 2018. The reason data science is critical now, said Caserta, is that the costs of compute and storage are dramatically lower than just a few years ago; data generated by all aspects of society has increased; and there is a need to efficiently learn what there is to know about our data.
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