A central challenge in transforming a ponderous Big Data headache into an agile Big Analysis win is finding a way to scale (often spelled S-U-P-P-O-R-T) Tableau users with the data they seek to visualize. Like most coins, there are two images we can observe – one from the perspective of the data analyst visualizing in Tableau and one from the data manager who structures and provisions data tables worth visualizing.
3 days, 10,000 attendees, multiple TED speakers… but this wasn’t a motivational sales conference. It was a conference for data geeks – the Tableau Conference. In this case, what happened in Vegas will NOT stay in Vegas. It needs to be shared.
Work in or with technology much and you’re likely to know the impact that the forces of democratization can accomplish. Broadening the effective population that can perform an essential task – without resorting to agency or hand-holding – has been at the heart of most business ‘disruptions’ of the Internet Era. There’s an emerging dynamic in the convergence of Big Data and democratized access to data analytic tools, like Tableau.
Pundits who focus on BI and Big Data consistently estimate that roughly two-thirds of any BI initiative is spent profiling and identifying the data that will be used for analysis. As a recovering data analyst – “Hi, my name is Lee. I’m a statistician” – I appreciate their focus on the most time-consuming element in living the quantitative dream.
How Enterprise Search and Big Data Find Common Purpose
Forrester’s 2015 Wave on Search and Knowledge-based Discovery is out, offering a fresh perspective on the evolution of search-based applications. We are pleased that Forrester designated Attivio as a Leader in this category and that the evolution described suggests an important connection between next-generation search and the opportunities of Big Data.
If you’re currently waiting for data to analyze or you’re working to find data for a colleague – you’re familiar with one of the productivity challenges associated with getting BI from Big Data. Finding the right information and provisioning it for analysis and decision-making constitutes a real bottleneck for many organizations.
My last two posts highlighted both a recent change and a long-standing challenge. That no fewer than ten thousand Investment advisory firms face AML regulation – where the costs of compliance have increased by more than 50% over the last three years – suggests the potential for a messy regulatory train-wreck. Why are costs spiraling out-of
Between 2011 and 2014, banking respondents to KPMG’s Global Anti-Money Laundering Survey reported an average increase in AML compliance costs of 53%. That average exceeded both their 2011 prediction (40%) and the previous (2007-2011) average of 45%. In seven years, institutions seem to have made very modest headway in cost-efficiently complying with regulatory changes. Are there reasons and solutions?