Informatica

Informatica

Informatica

Shorten time to value

As the pace of business speeds up and the velocity of data from the Internet of Things increases, organizations are finding it increasingly difficult to capture and process big data in real time without either expensive, manual processes or the integration of fragmented point solutions.

Both introduce complexities for IT and corresponding delays delivering data to the business. Organizations need to shorten the time to value for enterprise cloud-ready data lakes so they can:

•     Drive profitability
•     Uncover opportunities
•     Detect problems
•     Accelerate innovation
•     Deliver exceptional customer experiences.

c09-big-data-building
According to a Bain & Co. survey, 59% of organizations believe they lack the capabilities to generate meaningful business insights from their data.

A systematic approach to big data management enables you to quickly and repeatably get more business value from more big data without more risk.

Cloud-ready from day one

Support doesn’t stop at popular on-premises Hadoop distributions. Thanks to out-of-the-box connectivity to cloud databases, cloud data stores, and cloud applications, you can truly turn any data into trusted data assets anywhere.

Rapid-fire insight delivery

Informatica’s library of hundreds of prebuilt connectors and simplified stream processing on top of open-source and proprietary streaming engines let you integrate nearly any data anywhere. Support for Tableau Data Extracts and a hub-based publish/subscribe architecture also let you repeatably deliver more data faster to more data targets.

Self-service governed data

Informatica’s self-service data preparation enables faster business access to more trusted insights so the right people get the right data at the right time. It includes:

•     Built-in data lineage
•     Enterprise-wide data asset discovery
•     Smart data set recommendations
•     Crowdsourced data asset tagging and sharing

Sensitive data detection

Informatica’s risk-centric approach to protecting big data automatically classifies sensitive data and proactively detects threats of unauthorized data access or proliferation. Based upon assessments, data can be non-intrusively protected for secure access to contextual information.