Business Intelligence Strategies for the CIOEmail Alerts
-
'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. Analysis
-
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. Analysis
-
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. Analysis
-
'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. Analysis
-
2011 business intelligence (BI) challenges survey
Survey Slide Show
-
Advanced analytics programs focused on budgeting, marketing
Survey Slide Show
-
Data analytics software challenges: Tying results to actions
Survey Slide Show
-
'Analytics in Action' Virtual Seminar
SearchBusinessAnalytics.com presents a free virtual seminar designed to help participants create an effective analytics and business intelligence strategy. Listen on-demand at your convenience. Virtual Seminar
-
Test time: What do you know about 'big data' technologies?
Take this short quiz to test your understanding of ‘big data’ technologies, use cases and management issues – plus get recommendations for additional reading on big-data topics. Quiz
-
'Big data' analytics: Tapping into transactional data -- and more
In this video Q&A series, business intelligence experts and IT vendor executives explain "big data" technologies and use cases and give tips on how to get started with big-data analytics. Video guide
- See More: Essential Knowledge on Business intelligence data mining
-
Startup launches 'temporal analytics' engine to visualize Web
A small startup has developed a “temporal analytics” engine, which sifts 100,000 Web pages an hour, extracting data and associating it to time. But can it also predict the future? News | 20 Feb 2012
-
From the Editors: Getting started on a 'big data' analytics program
Does your organization have a firm grasp on what "big data" is? That's a good place to begin on a big data analytics project, but don’t forget about basic IT blocking and tackling. From the Editors | 31 Jan 2012
-
Q&A: Effective predictive modeling techniques more than a math problem
In an interview, analytics and data mining consultant John Elder offers advice on managing successful predictive modeling initiatives and a head’s up on common mistakes to avoid. News | 12 Jan 2012
-
Building predictive models requires business engagement, mix of skills
To generate useful predictive analytics results, predictive modeling teams need a combination of analytical and business know-how plus close ties to business users, say analytics pros and consultants. News | 10 Jan 2012
-
Biggest business intelligence software stories of 2011
From the explosion of "big data" analytics to data quality issues plaguing business intelligence (BI) programs to data mining privacy concerns, there was no shortage of must-read BI stories in 2011. Photo Story | 04 Jan 2012
-
Skills shortage, training present pitfalls for 'big data' analytics
A shortage of skilled data scientists and a user-unfriendly set of technologies are the biggest obstacles impeding big data analytics programs, say analysts and IT professionals. News | 01 Jan 2012
-
Best practices for 'big data' analytics rely on familiar disciplines
The terrain may seem foreign, but many proven data management and business intelligence best practices translate well to big data analytics programs, according to analysts. News | 30 Dec 2011
-
From the Editors: Looking back, looking ahead on advanced analytics
Big-data analytics and other forms of advanced analytics will be a big battleground for BI vendors in 2012. Our recent coverage highlights that, and ways users can up their analytics game. From the Editors | 22 Dec 2011
-
Q&A: Lack of trust in predictive analytics models can snarl projects
In an interview, predictive analytics consultant Eric Siegel offers advice on building organizational trust in the findings of predictive models -- and warns how the process can go wrong. Q&A | 16 Dec 2011
-
LinkShare explains why it dumped DB2 for the Exadata database machine
LinkShare’s BI director says the need for scalability was a key factor in moving the affiliate marketing company’s data warehouse to Oracle Exadata. Q&A | 15 Dec 2011
- See More: News on Business intelligence data mining
-
What is social media analytics software, and what does it do?
Learn the basics of what social media analytics software is and how it and text analytics can benefit companies. Get a definition of and use case for social media analytics. Answer
-
Customer data you should collect for your customer analytics program
Every piece of customer data you can collect is potentially important to your customer analytics program, according to customer data analytics expert Richard Snow. Find out why. Answer
-
Analytics and integration software for collecting customer data
If you’re collecting customer data for analysis, learn about options such as data integration technology and third-party systems for collecting customer data from external sources. Answer
-
Is your company primed for social media analytics?
Are some companies primed to get more use out of social media analytics than others are? Find out, plus learn how a social media analytics strategy compares to BI strategies. Answer
-
What are the top business intelligence software tools for SMBs?
Get expert advice on finding the top business intelligence software for small and -to-medium-sized companies. Plus, learn the best way to choose an analytics or BI SMB tool. Answer
-
Examining different data access methods: OLAP and data mining
Learn about the different types of data access methods including OLAP and data mining, find out about using query languages to access data warehouses and SQL and OLAP's role in accessing data. Ask the Expert
-
Building a career in data warehousing/business intelligence
How can you start a career in the data warehousing/business intelligence (DW/BI) space? Find out in this expert response. Ask the Expert
-
Data mining uses in vertical industries
Get examples of how data mining is used in vertical industries, such as retail, manufacturing, healthcare, financial and telecommunications. Ask the Expert
-
Data warehousing, data mining and data querying: Terms and definitions
Learn the difference between data warehousing, data mining and data querying. Ask the Expert
-
Data mining in the healthcare industry
Learn the advantages of data mining in the healthcare industry, according to our analytics expert, William McKnight. Ask the Expert
- See More: Expert Advice on Business intelligence data mining
-
big data analytics
Big data analytics is the process of examining large amounts of different data types, or big data, in an effort to uncover hidden patterns, unknown correlations and other useful information. Definition
-
data scientist
A data scientist is an emerging title in the fields of data management and analytics that generally refers to a highly skilled employee capable of diving into large data sets, filtering out the noise and finding the nuggets that will help to deliver ... Definition
-
deep analytics
Deep analytics is the application of sophisticated data processing techniques to yield information from large and typically multi-source data sets comprised of both unstructured and semi-structured data. Definition
-
association rules (in data mining)
Association rules are if/then statements that help uncover relationships between seemingly unrelated data in a transactional database, relational database or other information repository. Definition
-
in-memory analytics
In-memory analytics queries data residing in a computer’s random access memory (RAM) rather than data stored on physical disks. Definition
-
business analytics (BA)
Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis. Business analytics is used by companies committed to data-driven decision making. Definition
-
ad hoc analysis
Ad hoc analysis is the term commonly used in businesses to describe a product (analytical report, statistical analysis or model, or other report or summary of data) produced one time to answer a single, specific business question. Definition
-
opinion mining -sentiment mining
Opinion mining is a process for tracking the mood of the public about a certain product, for example, by building a system to examine the conversations happening around it. Definition
-
noisy data
Noisy data is meaningless data. The term was often used as a synonym for corrupt data, but its meaning has expanded to include data from unstructured text that cannot be understood by machines. Definition
-
unstructured data
Unstructured data is a generic label for describing any data that is not in a database. Definition
-
Top five biggest business intelligence (BI) software stories of 2011
From the explosion of "big data" analytics to data quality issues plaguing business intelligence (BI) programs to data mining privacy concerns, there was no shortage of must-read BI stories in 2011. Photo Story
-
Why you should keep your 'big data' technology small -- for now
In a video interview at the Strata Conference 2011, Forrester Research analyst James Kobielus explains why it’s important for companies with big-data installations to optimize their storage systems. Video
-
Business data analytics tools: benefits, challenges and advice
Get an overview of the potential benefits of using data analytics software and common challenges involved in deploying analytics tools from Ventana analyst David Menninger. Podcast
-
Understanding complex event processing software
Complex event processing software can help companies act on major business events in real time. Learn more about CEP technology and get an overview of the CEP vendor market. Podcast
-
An introduction to today’s advanced data analytics technology options
Get an overview of advanced data analytics software, including a discussion of the potential uses of analytic technology and advice on creating an advanced analytics strategy. Podcast
-
Has business intelligence (BI) technology become a commodity?
Consultant Mark Madsen discusses the state of business intelligence (BI) technology adoption and maturity. Video
-
Use data analytics to make better business decisions
Listen to a Q&A with Accenture's Jeanne Harris and learn how to put data analytics to work in your organization. Podcast
-
'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. Analysis
-
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. Analysis
-
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. Analysis
-
'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. Analysis
-
Startup launches 'temporal analytics' engine to visualize Web
A small startup has developed a “temporal analytics” engine, which sifts 100,000 Web pages an hour, extracting data and associating it to time. But can it also predict the future? News
-
From the Editors: Getting started on a 'big data' analytics program
Does your organization have a firm grasp on what "big data" is? That's a good place to begin on a big data analytics project, but don’t forget about basic IT blocking and tackling. From the Editors
-
Q&A: Effective predictive modeling techniques more than a math problem
In an interview, analytics and data mining consultant John Elder offers advice on managing successful predictive modeling initiatives and a head’s up on common mistakes to avoid. News
-
Building predictive models requires business engagement, mix of skills
To generate useful predictive analytics results, predictive modeling teams need a combination of analytical and business know-how plus close ties to business users, say analytics pros and consultants. News
-
big data analytics
Big data analytics is the process of examining large amounts of different data types, or big data, in an effort to uncover hidden patterns, unknown correlations and other useful information. Definition
-
Biggest business intelligence software stories of 2011
From the explosion of "big data" analytics to data quality issues plaguing business intelligence (BI) programs to data mining privacy concerns, there was no shortage of must-read BI stories in 2011. Photo Story
- See More: All on Business intelligence data mining
About Business intelligence data mining
Data mining has many benefits but is a complex discipline that's constantly evolving. Stay up to date on the data mining market with articles about data mining and business intelligence news, trends, research and software. Get an introduction to data mining and learn about predictive data mining and other data mining concepts and methods, plus learn how to successfully evaluate and deploy data mining software tools, solutions, technology and reports. Check out exclusive data mining case studies addressing a variety of industries and business problems, such as medical data mining and CRM data mining. Read examples of business intelligence and data mining best practices and successful tools and techniques, and stay on top of new data mining technology and terms, such as machine learning, data mining visualization, data mining clustering and neural networks data mining.