Tag: Data Preparation

Improve your company’s bottom line with analytics

The explosion of data in the financial services industry is creating new opportunities for business intelligence and analytics. At the same time, this explosion presents significant challenges. Over 2.7 zettabytes of data exist in the digital universe today. Every day, financial services companies seek to use these massive volumes of data to increase margins, reduce risk, boost customer satisfaction, and win in a globally competitive marketplace.

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Cloud Analytics: Your Key to Modern BI Capabilities that Drive Business Success

In The Forrester Wave™: Enterprise BI Platforms With Majority Cloud Deployments, Q3 2017, Forrester Principal Analysts Boris Evelson and Martha Bennett noted that, “The winners in the digital economy will be those that are able to gain insights the fastest and take appropriate action. To do so, companies need a solid data and analytics foundation, and cloud-based BI platforms are an essential part of this foundation.” In fact, among those organizations that Forrester surveyed in 2017, 45% said that they had “either already moved some or all of their BI capabilities to the cloud or were planning to do so.”

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Making Decisions with Data – Is Data Prep Really Preparing You for Success?

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Data preparation is an essential tool for everyone who wants to get value from sources of information. Whether this data is held in internal applications, derived from partners or supplied by third parties, it will need some work before it can be analysed. More importantly, prepared data must be connected and related to other analytic instances in the enterprise, so teams can collaborate and make better decisions with data.

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Making Decisions with Data – The Role for Data Preparation

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Making use of data within companies is one of those challenges that should deliver huge results. In its FutureScape predictions for 2016, analyst firm IDC estimated that, worldwide, those companies analyzing all their information for actionable insight should see an extra $430 billion in productivity gains, compared to those that did not look at all their data.

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