Business intelligence project management
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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.
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Business intelligence project management News
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March 08, 2017
08
Mar'17
Analytics teams give data science applications real scientific rigor
Data scientists at companies such as LinkedIn and Cisco are applying aspects of the scientific method to data mining and analysis initiatives to try to make sure they get valid results.
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February 28, 2017
28
Feb'17
Successful data science process not simple to set up, sustain
Data science teams face a mix of process and cultural challenges in organizations, according to experienced analytics managers who offer advice on how to overcome the hurdles.
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February 06, 2017
06
Feb'17
Don't learn lessons on predictive modeling techniques the hard way
Deploying and using predictive modeling tools without heeding best practices doesn't guarantee analytics success, a fact that many analytics managers and election forecasters know all too well.
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October 06, 2016
06
Oct'16
Visualized data aids in building, updating predictive models
Data scientists at Capital One and BuildingIQ use data visualizations to help guide their efforts in developing, training and modifying predictive models for use in advanced analytics applications.
Business intelligence project management Get Started
Bring yourself up to speed with our introductory content
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How predictive analytics techniques and processes work
Predictive analytics is no longer confined to data scientists and other highly skilled analysts. But other users need to understand what it involves before they start building models. Continue Reading
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Tableau data governance policies key to enterprise use
Usage and data governance policies are vital to effectively implementing Tableau and avoiding common pitfalls that can affect deployments of the self-service software, experienced users say. Continue Reading
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Ten steps to start using predictive analytics algorithms effectively
A successful predictive analytics program involves more than deploying software and running algorithms to analyze data. This set of steps can help you put a solid analytics foundation in place. Continue Reading
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Siemens uses process mining software to improve manufacturing visibility
Prior to implementing process mining tools, manufacturer Siemens had little visibility into production bottlenecks and other operational issues. Now, it can see the sources of the problems more clearly. Continue Reading
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Eight reasons why business intelligence implementation can fail
BI tools can be very beneficial to an organization by delivering helpful insights, but common mistakes frequently derail their effectiveness and render them useless. Continue Reading
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Hike use of business intelligence via the Eisenhower Matrix
IT managers must work closely with the business to increase the number of people using BI tools in companies -- and a time management framework bearing the name of Dwight Eisenhower can help. Continue Reading
Manage Business intelligence project management
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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Better Tableau implementation gives BI dashboards a boost
Building good Tableau dashboards is about more than just pretty visualizations. Users say the process should incorporate strong data management practices and a sharp business strategy. Continue Reading
Problem Solve Business intelligence project management 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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Many businesses use BI reporting systems wrong, but they can improve
Many businesses commit similar mistakes when creating BI reports. Consultant Mico Yuk offers tips to help you avoid some of the most common pitfalls. Continue Reading
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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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Customer data analytics teams take on a more lawyerly look
In some organizations, corporate lawyers are tasked with protecting data from analytics abuse. But they need to avoid tying the hands of data scientists. Continue Reading