Trust, Time-to-Insight and Data Discovery
Digital transformation and IT modernization initiatives continue to be hot topics in the boardroom across nearly every industry, no matter the size of the organization. The goals are grand and the scope is broad—necessary to drive large visionary changes.
As we’ve witnessed from industry leaders who’ve disrupted their markets, the chances for success to drive transformational changes are greatly increased when rooted in the fundamentals: data and analytics. Typically, when the discussion turns towards cloud analytics modernization, much of the focus is on cloud data lakes, cloud data warehouses and self-service analytics platforms. And yes, these are all critical and necessary elements required to modernize an analytics initiative. But the root of analytics modernization initiatives is data.
No matter how modern your modern analytics platform is, unless your business users can find, trust and quickly leverage their data assets throughout the enterprise, your analytics modernization initiative will probably deliver underwhelming results. Furthermore, better analytics insights are realized when data is viewed with greater context, which means that common data sets (e.g., sales data, lead conversion data, etc.) are enriched with related data sets.
But, herein lies the problem: while the enterprise has all of the necessary data to drive a modern analytics initiative, the likelihood of the data analyst or data engineer having the right data is slim. Why? Mostly because they may not know that the data even exists in the enterprise.
In a BARC Institute Information Culture survey, 40 percent of respondents used less than 5 internal data sources and 56 percent of respondents used less than 5 external data sources. With the average enterprise having hundreds—if not thousands—of data sources, looking for high-quality data can be like trying to find a needle in a haystack.
To ensure the most impactful analytics downstream that drive significant business value, it starts at the very beginning: the raw data sources. Progressive enterprises will equip their data analysts and data engineers with the process, tools and access to explore their company’s data assets. If “data is the new oil,” then the data analysts and data engineers must be given the ability to perform a comprehensive survey before they start “drilling” to tap into most profitable data oil fields.
Data cataloging is an essential component for a modern analytics initiative, supporting self-service discovery and access to data. It provides the means to explore a company’s data assets in a secure and governed fashion, ensuring that all IT and regulatory compliance requirements are adhered to. And if the company is savvy and forward-thinking, they will implement a data cataloging solution that also leverages the wisdom of the cloud’s best practices, which includes tagging, ratings, comments and the ability share. Further, data catalog solutions driven by rich metadata will be able to provide contextual recommendations on related data sets and data lineage, which of course will be very helpful in delivering analytics with greater context.
Finally, analytics modernization is more than simply having a data catalog solution in the enterprise. It must be part of the complete end-to-end analytics process, where a business begins to measure discovery-to-insight as part of the value chain. When a data catalog solution, data integration platform,\and self-service analytics tools are implemented together on top of a modern data warehouse or data lake in the cloud…now we’re talking complete analytics modernization.
To help organizations on their analytics modernization journeys, Informatica has partnered with Tableau and AWS to bring you an integrated solution: the Tableau and Informatica Cloud Analytics Modernization on AWS, supported by an AWS Quick Start.
How do you get started? The solution has a free trial in the AWS Quick Start, so you can experience it firsthand. What’s included? The free trial comes with sample data and a use case to demonstrate how products from the three companies can be used together to modernize cloud analytics.
To learn more, read the solution brief or try the Cloud Analytics Modernization with AWS, Tableau and Informatica solution today.