Business analysts and line-of-business (LOB) data users have plenty of robust, self-service BI tools at their disposal. What they often lack is a way to get all the most relevant data into those tools. In a TDWI Checklist Report, Dave Stodder, Director of TDWI Research for Business Intelligence, lists seven best practices for executing a successful data science strategy. Number five: Give Data Science Teams Access to All the Data.
Some Attivio folks flew to the annual Gartner BI event last week to take the pulse of Business Intelligence, data discovery, and data democratization. We wanted to hear the latest from Gartner thought leaders and the several thousand data practitioners. In the opening keynote, there were 5 key takeaways. I’d like to zero in on numbers 2 and 3.
In a recent blog post about data exploration, Forrester's Boris Evelson discusses Tableau's recent acquisition of HyPer. He notes that HyPer addresses Tableau's previous lack of in-memory data exploration capability.
According to the latest evidence, The US Treasury estimates that over $300 billion in money laundering flows through casinos annually. The two leading sources of funds, fraud or drug trafficking, account for just over $64 billion alone. Recently, officials at the federal Financial Crimes Enforcement Network (FinCEN) – the agency responsible for monitoring casino operator compliance with the Bank Secrecy Act of 1970- have stepped up their AML compliance rhetoric and activity. And they’re not alone.
Occasioned by the announcement of a consent order with Florida bank Gibraltar Private Bank and Trust, the Office of the Comptroller of the Currency (or, OCC) announced two significant updates to its policies and procedures for calculating civil money penalties for non-compliance or persistent, uncorrected BSA/AML compliance. The OCC took the opportunity to call-out failures in the Gibraltar response to earlier orders - setting clearly tougher expectations for under-performing or unresponsive compliance programs.
Two or three years ago, when Big Data had started to gain serious traction in large enterprises, there was a rush to hire data scientists. Of course, disagreement reigned about what credentials made a true data scientist. Wonky math geeks were a good place to start. The rush to hire data scientists echoed the trend some decades earlier when investment firms hired quants right out of college and put them in the basement to create trading algorithms.
One thing was clear though. Data scientists were scarce and expensive.
Most chief executives have dreamed of leadership that permeates their organizations at every level. Yet to have that, every decision maker from the C-suite down would need data. And they fear that such data democratization may invite anarchy.
Despite that fear, their dream persists, and for good reason. Organizations with democratized data tend to have more buy-in, people at all levels take more responsibility, and their ideas are more relevant, with a greater chance of real impact. They feel stronger loyalty. Overall, there’s just plain smarter decision making.
Another fiscal year has come to a close, and we at Attivio have never been more excited about what’s to come. Our entry into the Big Data market is filling a void that enterprises struggle with every day.
We understand that data is a strategic asset that, when made accessible to everyone in the organization, can lead to smarter, faster decisions, pushing past the competition in ways that didn’t seem possible.