Roundup Of Analytics, Big Data & Business Intelligence Forecasts And Market Estimates, 2014
From manufacturers looking to gain greater insights into streamlining production, reducing time-to-market and increasing product quality to financial services firms seeking to upsell clients, analytics is now essential for any business looking to stay competitive. Marketing is going through its own transformation, away from traditional tactics to analytics- and data-driven strategies that deliver
The best big data technologies
Hadoop This is an open source platform which normally stores massive datasets through clusters. Hadoop supports both structured and unstructured data and scales without any hassle, making it a great option for companies likely to need extra capacity at short notice. This platform can also handle a huge number of tasks without latency. Overall, it's a great option for organisations with the develop
Big Data Analytics: Descriptive Vs. Predictive Vs. Prescriptive | InformationWeek
10 Biggest Tech Disappointments Of 2013 10 Biggest Tech Disappointments Of 2013 (click image for larger view and for slideshow) The majority of raw data, particularly big data, doesn't offer a lot of value in its unprocessed state. Of course, by applying the right set of tools, we can pull powerful insights from this stockpile of bits. In any big data setup, the first step is to capture lots of di
The Current State of Machine Intelligence
(The 2016 Machine Intelligence landscape and post can be found here) I spent the last three months learning about every artificial intelligence, machine learning, or data related startup I could find — my current list has 2,529 of them to be exact. Yes, I should find better things to do with my evenings and weekends but until then… Why do this? A few years ago, investors and startups were chasing
@things-about-r · Data * Science + R
Scatter Plots with Marginal Densities - An Example for Doing Exploratory Data Analysis with Tableau and R One of the first stages in most data analysis projects is about exploring the data at hand. During this stage the analyst tries to get familiar with his dataset by looking at summary statistics, feature distributions and relationships between different attributes - just to name the key tasks.
For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights (Published 2014)
Monica Rogati, Jawbone’s vice president for data science, with Brian Wilt, a senior data scientist.Credit...Peter DaSilva for The New York Times Technology revolutions come in measured, sometimes foot-dragging steps. The lab science and marketing enthusiasm tend to underestimate the bottlenecks to progress that must be overcome with hard work and practical engineering. The field known as “big data
AI-Powered Graph Database for Real-Time Analytics & Connected Data | TigerGraph
Fraud Detection Entity Resolution Anti-Money Laundering (AML) Product Recommendations Customer 360 Supply Chain Management Cybersecurity Threat Detection Financial Crime TigerGraph is the enterprise leader in AI and graph database technology, delivering unlimited parallel storage and computation to power your most critical business needs—from fraud detection, entity resolution, KYC/AML, and more.
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