Business intelligence data mining
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Staff Pick: The Rising Need for Analytics Accuracy
Learn how LinkedIn overcame analytics bottlenecks, 3 data modeling flaws that cripple data science projects, and common roadblocks of advancing data science teams and hiring data pros.
Business intelligence data mining News
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March 23, 2018
23
Mar'18
Cambridge Analytica-Facebook case shows need for ethical data mining
Ethical data collection practices are becoming even more important, as cases like Cambridge Analytica's misuse of Facebook data challenge consumer trust in enterprise analytics.
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November 21, 2017
21
Nov'17
Microsoft Azure cloud database activity takes off at Connect();
Microsoft Connect(); 2017 saw the addition of MariaDB and Cassandra to the Azure cloud database lineup. Also discussed: A set of Spark-based analytics services called Azure Databricks.
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November 09, 2017
09
Nov'17
Microsoft boosts SQL Server machine learning services
Python and R are among the tools in the SQL Server machine learning toolkit. Native T-SQL scoring is also on the agenda, as uncovered at PASS Summit 2017.
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November 06, 2017
06
Nov'17
Power BI updates drive Microsoft's latest hybrid cloud efforts
At PASS Summit 2017, Microsoft Azure's strides were measured in steps. These include Power BI updates that bring cloud reporting services down to earth.
Business intelligence data mining Get Started
Bring yourself up to speed with our introductory content
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decision-making process
The decision-making process, in a business context, is a set of steps taken by managers in an enterprise to determine the planned path for business initiatives and to set specific actions in motion. Continue Reading
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Three ways to turn old files into Hadoop data sets in a data lake
Hadoop data lakes offer a new home for legacy data that still has analytical value. But there are different ways to convert the data for use in Hadoop depending on your analytics needs. Continue Reading
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unstructured data
Unstructured data is information, in many different forms, that doesn't hew to conventional data models and thus typically isn't a good fit for a mainstream relational database. Continue Reading
Evaluate Business intelligence data mining Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Data scientist vs. business analyst: What's the difference?
Data science and business analyst roles differ in that data scientists must deep dive into data and come up with unique business solutions -- but the distinctions don't end there. Continue Reading
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Exploring Microsoft R Open, R Server for advanced analytics
Learn about the features and components of the Microsoft R family of predictive analytics tools, which includes Microsoft R Open, Microsoft R Client and Microsoft R Server. Continue Reading
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Customer insight among the business benefits of a marketing data lake
In this video, Sumit Sarkar from Progress Software discusses the benefits of a marketing data lake and explains how companies can determine what data to feed into a data lake. Continue Reading
Manage Business intelligence data mining
Learn to apply best practices and optimize your operations.
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Predictive analytics projects can bolster business decisions
Blind faith in predictive models can result in flawed business decisions. Analytics teams need to manage predictive processes carefully to keep things on the right track. Continue Reading
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Five steps to build better predictive analytics applications
Predictive analytics initiatives must be planned and managed effectively to ensure that they don't miss the mark on meeting business needs. Here's an approach to help keep them on track. Continue Reading
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Microsoft technology refresh touches SQL Server, integration tooling
Microsoft is at work on a delicate technology refresh affecting database tuning and architecture, as well as data integration and business intelligence. Continue Reading
Problem Solve Business intelligence data mining Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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Apply data science models effectively, not just for their own sake
Having data scientists build analytical models doesn't do much for an organization if the models don't help generate business benefits. Here are some ways to make sure they do. Continue Reading
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Advanced analytics tools extract business value from big data
Big data environments based on technologies such as Hadoop and Spark are being deployed more widely -- and the same goes for advanced analytics tools that can help organizations make effective use of the data flooding into those systems. In fact, ... Continue Reading
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LBS technology expands customer service, business operations
Many modern consumers and workers are always tuned-in to the digital world. They have laptops, tablets and smartphones that chirp and beep away with incoming messages. Those devices are also sending out information -- tweets and texts, yes -- but ... Continue Reading