If you’re like most business people, you invest in data analytics to uncover hidden connections, unseen correlations, unknown customer preferences, and other useful information.1 Maybe you want to make better decisions about which products and services will delight customers, or perhaps you want to uncover process changes that could cut costs and shorten time to market.
The next generation of analytics will let you see patterns for predicting future behaviors, not just analyzing those in the past.
But if you think you’ll find concealed insight with just self-service data visualization tools, data warehouse appliances, and Hadoop, you’re wearing blinders. The truth is, none of these technologies by themselves will fix bad data.
To make better decisions, you need great data—trustworthy, usable data that’s refined so you spend more time analyzing and less time finding and fixing errors. The risk of working with incomplete, inconsistent, untimely data is clear:
Our data platform works with any analytics ecosystem, any size data, and with any data source. Our self-service data preparation is flexible enough to support new technologies like Hadoop. And our framework can reuse work and skills across all analytics solutions—like traditional data warehouses.
That’s right, data warehouses. Let’s debunk that myth right now: The data warehouse is not dead. In fact, 70 percent of businesses are increasing spending in this area. What's challenging traditional data warehouses is the sheer complexity of data, and we have solutions that will scale. Your data analytics capabilities are only as reliable as the data going into them. Which means preparing your data to be complete, safe, and trustworthy is as crucial as analyzing it to support better decision making.
Informatica’s data integration and data quality solutions bridge the gap between raw, messy data and reliable analytics. We allow our customers to:
Our data platform works with any analytics ecosystem, any size data (small, medium, and big data), in any place (on premise or in the cloud). You get a self-service experience for data preparation that is flexible enough to support new technologies like Hadoop. You also get a framework that reuses work and skills across all analytics solutions—like traditional data warehouses, a data warehouse appliance, or even Hadoop.
Your data analytics capabilities are only as reliable as the data going into them. Which means preparing your data to be complete, safe, and trustworthy is as crucial as analyzing it to support better decision making.
1Survey Analysis: Big Data Investment Grows but Deployments Remain Scarce in 2014, Gartner, Inc., September, 2014
2Forrester webinar: Big Data Integration Gains Momentum: Are You Ready?, June, 2014
Jumpstart, scale, and ensure the on-going success of your data warehouse deployment.
Take data of any type or size and turn it into actionable insights that have maximum business impact.
Refine your data to drive real-time analytics and empower IT organizations to meet SLAs and goals like never before.
Capitalize on your data to drive business value, improve operational efficiency, and uncover smarter ways to engage customers.
Cut the number of point connections going from data sources to marts and warehouses.
TEB uses trusted data to build and extend customer relationships and enhance operational efficiency.
Tinkoff Bank acquires and retains more customers at a lower cost with Informatica Big Data Management.
Western Union built a data platform based on Hadoop and Informatica Big Data Edition