Features

Features

• Social media data analysis spans a spectrum of business uses

  Different facets of the social media analytics process offer different types of information to businesses looking to monitor social networks and analyze their own social media strategies.  Continue Reading

• Eliminate inconsistent data by ousting its evil twin sisters

  Data quality problems, often resulting from inconsistent data definitions and duplicates, can hamstring BI and analytics efforts if they aren't forcefully addressed.  Continue Reading

• A view from the chief analytics officer

  The chief analytics officer is the newest data-focused executive. One financial company's CAO sizes up the state of analytics.  Continue Reading

• Managing big data: The two biggest mistakes companies make

  Many organizations are setting their big data analytics efforts up for failure by plunging ahead without proper planning upfront, says book author Keith B. Carter.  Continue Reading

• The future of analytics lies in open source technology

  All the excitement of analytics professionals today is attached to open source tools. Author Cory Isaacson explains why.  Continue Reading

• Big data analytics projects raise stakes for predictive models

  Before starting the analytical modeling process for big data analytics applications, organizations need to have the right skills in place -- and figure out how much data needs to be analyzed to produce accurate findings.  Continue Reading

• Sounders coach shows way ahead for analytics in sports

  The Seattle Sounders fitness coach is taking sports analytics into uncharted territory and scoring some big wins along the way.  Continue Reading

• Big data benefits begin with business focus in analytical modeling

  Big data analytics programs need a strong analytical modeling foundation to deliver the business benefits that companies are looking for. And that starts with tight ties between analytics teams and business units.  Continue Reading

• Location-based analytics helps Wendy's find its way to new sites

  Most people remember geography class as a liberal arts concentration. But John Crouse of Wendy's is showing that geographic knowledge can make for a valuable pairing with statistical analysis as part of location intelligence efforts.  Continue Reading

• Location-based analytics helps orgs zero in on gains

  Location-based analytics may be overlooked right now, but users expect this mapping technology to play a huge role in the future of business.  Continue Reading

• Why 'logical data warehouse' is no longer a logical term

  Consultant Rick van der Lans contends that data warehouses are inherently logical and don't need to be qualified as such. What really matters, he says, is that they present an integrated view of enterprise data, no matter where it's stored.  Continue Reading

• Data visualization software deserves a deep look before buying

  Data visualization tools can present information to business users in easy-to-grasp formats. But it isn't a pretty picture if you buy the wrong one.  Continue Reading

• Author: Data mining projects depend on excavating meaningful data

  In a Q&A, book author David Nettleton offers advice on avoiding data mining pitfalls and pinpointing valuable business data to mine and analyze.  Continue Reading

• How to evaluate the viability of a data mining project

  In a book excerpt, author David Nettleton details questions to ask and factors to consider in weighing the potential benefits of data mining projects.  Continue Reading

• BI architecture needs extensions to meet new analytics demands

  Claudia Imhoff and Colin White outline a business intelligence environment designed to accommodate existing data warehouses and new technologies.  Continue Reading

• Data lake muddies the waters on big data management

  Barry Devlin argues against using the trendy term 'data lake' to describe a big data store for structured, unstructured and semi-structured data.  Continue Reading

• Businesses look for tech solutions to big data security issues

  The growing adoption of big data analytics applications is complicating data security challenges -- and creating a need for new security strategies.  Continue Reading

• Laws leave gray area between big data and privacy

  Laws on data collection and use remain foggy, leaving businesses to feel their way through big data and privacy laws.  Continue Reading

• Data collection practices spark debate on big data ethics, privacy

  The increasing emphasis on collecting and analyzing big data is driving a debate on whether tighter privacy rules are needed to protect customers.  Continue Reading

• Selecting the right SQL-on-Hadoop engine to access big data

  Rick van der Lans explains why it's important to evaluate the differences in the technologies that make it possible to access Hadoop data using SQL.  Continue Reading

• Developing business decision-making models that really work

  David Loshin defines weighting factors and offers advice for beginning a decision-modeling effort that ultimately leads to the best business outcome.  Continue Reading

• Close the deal on using CRM analysis to boost customer knowledge

  Customer relationship analysis holds the key to improved marketing and customer engagement. But it starts with having the right tools and skills.  Continue Reading

• Data visualization tools help users make sense of messy data

  Visualizing data makes it easier to grasp. But there's more to selecting and deploying data visualization software than creating catchy graphics.  Continue Reading

• Self-service analytics tools have value, carry risks

  There are risks to be aware of when business users take responsibility for self-service business intelligence, but there are ways to mitigate them.  Continue Reading

• Kaiser Permanente VP prescribes bigger role for healthcare data analytics

  Terhilda Garrido is at the head of a heightened effort by health system Kaiser Permanente to use analytics to improve its patient care delivery.  Continue Reading

• Loshin: Keys to managing better business intelligence programs

  In a Q&A, author David Loshin details how business intelligence managers can enhance BI success, from building dashboards to demonstrating value.  Continue Reading

• Defining and using KPIs in a successful business intelligence system

  In this book excerpt, author David Loshin discusses how to select key performance indicators and turn data into actionable knowledge for BI success.  Continue Reading

• Analytical models in big data environments often best left small

  In many cases, data analysts can find the results they're looking for by examining only a sample of the data that's available in big data systems.  Continue Reading

• Hadoop still too slow for real-time analysis applications?

  Hadoop vendors are trying to position the distributed processing technology as a real-time analytics tool. But some real-time roadblocks remain.  Continue Reading

• Download presentations from the BI Leadership Summit

  At the 2013 BI Leadership Summit, many of the industry's leading BI experts gathered to share vendor-neutral expertise and proven strategies.  Continue Reading

• Limited role for big data seen in developing predictive models

  Big data gets a lot of hype, but when it comes to developing predictive models, it may not be as useful as some think.  Continue Reading

• Prescriptive analytics takes analytics maturity model to a new level

  Consultant Jen Underwood explains what prescriptive analytics is and how it can help companies looking to optimize their decision making processes.  Continue Reading

• Handling the hoopla: When to use Hadoop, and when not to

  Hadoop has become everyone's big data darling. But it can only do so much, and savvy businesses need to make sure it's a good fit for their needs.  Continue Reading

• What location technology, and location intelligence, can do for you

  In today's mobile and data-rich world, there are an increasing number of ways location intelligence initiatives can generate business value.  Continue Reading

• Data visualization tools may be glamorous, but focus on business value

  Data visualization tools definitely possess a cool factor, but it's important not to get caught up in the glamour. Focus on business value first.  Continue Reading

• Location data finds a home in mobile business intelligence apps

  The combination of location intelligence and mobile BI tools can help users take analytics into the field, but there are challenges to be aware of.  Continue Reading

• Companies using Hadoop for analytics bring meaning to satellite data

  Companies are using Hadoop for analytics to uncover new meaning in satellite imagery and allow industries to gain new insights from geospatial data.  Continue Reading

• Predictive analytics software puts big squeeze on IT systems

  Predictive analytics projects can overpower IT systems, making it necessary for IT managers to provide appropriate support, storage and data control.  Continue Reading

• Cloud-based analytics still mostly on the horizon

  Business intelligence and advanced analytics applications have yet to make a big mark in the cloud, despite vendor efforts to push cloud analytics.  Continue Reading

• Match in-memory processing speed to big data analytics business need

  Michael Minelli, co-author of a book on big data analytics, says in-memory analytics tools must be tied to business processes to pay off for users.  Continue Reading

• Eckerson: Self-service business intelligence not a give-and-go affair

  In an interview, TechTarget's Wayne Eckerson explains why there's more to self-service BI success than putting tools in the hands of business users.  Continue Reading

• In-memory technology pushes analytics boundaries, boosts BI speeds

  In-memory appliances amp up business intelligence performance by moving processing off of disks. But cost and other issues need to be considered.  Continue Reading

• Seeking treasure from social media tracking? Follow the customer

  Social media analytics tools can help companies dig into layers of online customer data in search of business gold. But a human touch is needed, too.  Continue Reading

• The buzz: Social media analytics tools a must for many

  No doubt you've heard the term social media analytics -- it's the gathering and exploring of social media data. Do you need to invest now? It depends.  Continue Reading

• Self-service BI tools best fashioned with custom fit for diverse users

  Project managers must consider the unique needs of different groups of business users when implementing self-service business intelligence tools.  Continue Reading

• Real-time analytics brings BI data directly into business operations

  Giving end users immediate access to operational data for real-time business intelligence can help drive better decisions, if it fits business needs.  Continue Reading

• On-the-job training turns would-be lawyer into IT director for Condé Nast

  Whether it was 'dumb luck' or fate, Justin Glatz got pulled into IT and now manages business and corporate systems at publishing company Condé Nast.  Continue Reading

• Note to self: Business intelligence, analytics trends to watch in 2013

  Businesses will tackle big data analytics, cloud BI, consumerization and collaboration in the New Year alongside beloved classics like data quality.  Continue Reading

• Clutter, data overload put dashboard designs on path to failure

  Keep your BI dashboard project on track by avoiding common mistakes, such as design gimmicks, cluttered screens and irrelevant data.  Continue Reading

• New business trending topic: Monitoring social media, analyzing data

  Companies seeking customer insights are rushing to deploy social media monitoring and analytics tools. But first, make sure you know what to expect.  Continue Reading

• Data-driven culture helps analytics team generate business value

  Three analytics managers offer tips on engaging with business users and building strong analytical environments, as told to author Wayne Eckerson.  Continue Reading

• Creating effective analytical processes: Tips from analytics leaders

  Drawing on real-world examples, book author Wayne Eckerson summarizes the elements needed to implement a successful business analytics program.  Continue Reading

• Put consumer data privacy first -- analytics value will follow

  Data privacy and privacy policies are sensitive subjects, but done right, they may also create a competitive advantage.  Continue Reading

• For unwary users, social media data analysis can be an unfriendly task

  Organizations must take into account various obstacles when implementing social media analytics plans to ensure that they provide business value.  Continue Reading

• Using social media monitoring tools starts with business connections

  Companies implementing social media analytics programs need to keep the big picture in mind and tie the efforts directly to their business strategies.  Continue Reading

• Social media analytics software pulls useful info out of online muddle

  Companies can use social media analytics tools to distill business insights from the abundance of data on social networks. That's the goal, at least.  Continue Reading

• Data visualizations get more advanced -- and more complicated

  With data visualization tools offering more and more functionality, managing projects to visualize data is becoming a bigger challenge for BI teams.  Continue Reading

• Predictive analytics programs need open organizational minds

  Using predictive analytics tools can help companies move forward more intelligently, particularly when they welcome new ideas on business strategies and processes.  Continue Reading

• Mobile business intelligence brings benefits -- and barriers

  Developing and delivering mobile business intelligence applications poses various challenges that can derail a mobile BI strategy if not avoided.  Continue Reading

• Ability to explain analytical results vital to gaining executive buy-in

  They've purchased the analytics tools, but executives may not buy the results, especially if they don't understand what the numbers are saying.  Continue Reading

• Apache Hadoop spurs hopes but creates hardships for analytics users

  Described as cutting edge, hot, niche and hard to use, Hadoop, like all celebrities, has its shining moments and its dismal displays.  Continue Reading

• 'Big data' concept has grown well beyond its diminutive beginnings

  What is "big data" and why is the IT industry talking about it so much? IT pros offer insights into the origins of the popular and much-hyped phrase.  Continue Reading

• App47 selects Loggly over Splunk for log management

  Find out why mobile application management provider App47 chose up-and-comer Loggly over well-known Splunk for its log management needs.  Continue Reading

• NASA uses text analytics to bolster aviation safety

  NASA relies on numeric data to explain what incidents occur, but text data from incident reports and warning signals reveals why they do.  Continue Reading

• Social media analytics tools offer customer insights, but care needed

  While analyzing social media data can yield valuable information, consultants caution that the process is still a complex and inexact science.  Continue Reading

• Data sandboxes help analysts dig deep into corporate info

  Giving analytics professionals control of small amounts of space in data warehouses lets them experiment with data sets in a managed environment.  Continue Reading

• Riding herd on Excel BI use isn't easy, but it's necessary

  Eradicating the use of Excel in business intelligence applications turned out to be a pipe dream in most organizations. Now the focus is on controlling it -- as best you can.  Continue Reading

• 'Big data' analytics programs require tech savvy, business know-how

  Consultant Rick Sherman details the skill sets and roles that he thinks are vital to the success of "big data" analytics initiatives. Technical skills alone aren't enough, he says.  Continue Reading

• The wrong way: Worst practices in 'big data' analytics programs

  Consultant Rick Sherman details the biggest mistakes to avoid in planning and managing deployments of big data analytics tools, from focusing on the technology to overselling projects.  Continue Reading

• Five first steps to creating an effective 'big data' analytics program

  Choosing the right technology is only half the startup battle on "big data" analytics. Get a list of deployment tips from consultant Lyndsay Wise to help set your organization on the right path.  Continue Reading

• 'Big data' analytics projects easier said than done -- but doable

  Putting an effective "big data" analytics plan in place can be a challenging proposition. Consultant Lyndsay Wise offers her advice on what to consider and how to get started.  Continue Reading

• Managing multiple BI tools doesn't have to be so hard

  A multi-tool business intelligence environment may be the norm, but it’s not the ideal. Learn steps you can take to reduce the complexity and increase the effectiveness of your BI installation.  Continue Reading

• Applying agile methods to data warehouse projects

  Agile development processes can take a lot of the pain out of building data warehouses and enable project teams to deliver functionality, and business value, on a rolling basis.  Continue Reading

• Creating an advanced data analytics business culture: Tips and advice

  Data analytics can help drive better business decisions, according to users and analysts. But creating an analytics business culture usually requires high-level executive support.  Continue Reading

• The importance and benefits of operational decision making

  In this section of 'Smart (Enough) System', you'll learn the importance of operational decisions and different strategies that influence decision making. You'll also read about key BI terms including business agility, strategic alignment and ...  Continue Reading

• How to make operational decisions and data corporate assets

  In this excerpt, you'll find out why operational decisions matter to businesses and how to turn operational decisions into a corporate asset. You'll also learn about the five characteristics of effective operational decision making and what traits ...  Continue Reading

• Understanding benefits of business intelligence reporting, data mining

  Learn how to evaluate decisions, find trends and answer questions with data mining and business intelligence (BI) reporting. Find out how different management levels can use BI to reach their goals in this excerpt from a BI book.  Continue Reading

• Information and examples on data mining and ethics

  Learn about data mining and ethics and review ethical issues related to data mining, plus find information, data mining examples and sources from the book Data Mining: Know it All.  Continue Reading

• Simple data mining examples and datasets

  See data mining examples, including examples of data mining algorithms and simple datasets, that will help you learn how data mining works and how companies can make data-related decisions based on set rules.  Continue Reading

• What is a data rollup?

  Learn what a data rollup is and read about data rollup macro examples and case studies in this data mining tutorial from the book Data Mining: Know it All.  Continue Reading

• The difference between machine learning and statistics in data mining

  Discover the difference between machine learning and statistics and find out how generalization as search can be a data mining tool. Learn about the bias of the search, including information on language bias, search bias and overfitting-avoidance ...  Continue Reading

• Using data merging and concatenation techniques to integrate data

  Learn two data integration techniques, data merging and concatenation, and see how to combine and merge data sets in this excerpt from the book Data Mining: Know it All.  Continue Reading

• Calculating mode in data mining projects

  Learn tips for data mining, including how to work with data rollup for sums and averages, and learn about calculating mode, the key to event-driven architecture (EDA), in this tutorial from the book Data Mining: Know it All.  Continue Reading

• Data acquisition and integration techniques

  Find data mining methods and techniques including methods for data acquisition and data integration. Learn how to gather from different and types of data sources, plus get tips for data aggregation, rollup, sampling and data partitioning from Data ...  Continue Reading

• Understanding metrics for business process management

  Business processes are controlled by metrics. Learn more about business process management (BPM) and the role of metrics, in this book chapter for IT managers.  Continue Reading

• Business process management and IT process entities

  An IT process entity is a conceptional entity that's not a configuration item (CI). Learn more about process entities and business process management, with consideration of ITSM and ITIL.  Continue Reading

• What is Microsoft PerformancePoint Server 2007?

  Learn about Microsoft PerformancePoint Server 2007, including the basics monitoring, analysis and planning applications.  Continue Reading

• Managing unstructured data in the organization

  Learn about the challenges of unstructured textual data in the organization and get expert advice from Bill Inmon, in this free chapter download.  Continue Reading

• What is business process management?

  Learn about business process management (BPM) and get definitions of terms related to business process management.  Continue Reading

• Business process management: Basics and demystification

  Get the basics of business process management (BPM) and learn how to evaluate BPM vendor hype, in this free chapter download.  Continue Reading

• Successful business intelligence: The role of BI front-end tools

  Learn about the business intelligence front-end tools that are available to business users -- and how the right BI tool can lead to BI success.  Continue Reading

• Law enforcement data mining, predictive analysis: Terms, errors of data mining for violent crime

  Get definitions and explanations of data mining and predictive analysis terms, and learn four data mining errors to avoid in law enforcement -- or any in context.  Continue Reading

• Why are business intelligence professional titles confusing?

  TDWI research has shown that the average individual holds one primary role and three secondary roles. Each of these roles requires distinctive skills and knowledge.  Continue Reading

• Data mining: Three steps to mining unstructured data

  In this free chapter excerpt, learn a three-phase process to make data mining and analyzing unstructured data more streamlined and productive.  Continue Reading

• Customer intelligence: From data to dialogue

  Learn about the business value of customer intelligence and how customer intelligence is critical to building competitive advantage.  Continue Reading

• Introduction to data mining: Association analysis

  This excerpt from Introduction to Data Mining offers a crash course on association analysis -- an effective data mining technique.  Continue Reading

• Enterprise dashboards, design and best practices for IT

  Read this excerpt from Enterprise Dashboards, Design and Best Practices for IT written by Shadan Malik and discover how enterprise dashboards can be both SMART and have an IMPACT.  Continue Reading