What is your e-mail address?

My e-mail address is:

Do you have a password?

Forgot your password? Click here
close

On Demand

Fern Halper

Introducing the TDWI Big Data Maturity Model

Many end-user organizations are currently commencing or expanding solutions for big data and big data analytics. These organizations want to understand how to approach big data and where they stand relative to other companies, especially their competitors. In late October 2013, TDWI launched its Big Data Maturity Model Assessment Tool, which can help to guide IT and business professionals on their big data journey. The assessment looks at companies across five dimensions that impact maturity, including organization, infrastructure, data management, analytics, and governance.

Fern Halper, Krish Krishnan


David Stodder

Improving Agility with Business Intelligence and Analytics: A Preview of the Next TDWI BI Executive Summit and World Conference

Agility is a critical success factor for today’s enterprises. Agility is about being flexible and responsive to change, from the rapid shift in business conditions to new customer preferences. Business intelligence, analytics, and data warehousing projects must also show flexibility and deliver value sooner. In this Webinar, we highlight the upcoming TDWI World Conference and BI Executive Summit (August 18–23) in San Diego, and discuss recent agile-related research and best practices, as well as case studies and courses in analytics, BI essentials, and data analysis and design.

David Stodder


David Stodder

Data Visualization and Discovery for Better Business Decisions

Data visualization and visual data discovery can enable diverse types of users—from data scientists working with big data to nontechnical business managers and frontline users—to see significant trends and patterns in data that they would have struggled to see in voluminous tabular reports and spreadsheets. As big data volumes grow and organizations seek to integrate diverse and complex information, users’ ability to comprehend information quickly and put it to productive use hinges on data visualization.

David Stodder


David Stodder

The Doctor Is In: The Role of the Data Scientist for Analyzing Big Data

No profession is getting more attention these days than that of the “data scientist.” Data scientists have made the covers of business magazines and are practically rock stars at online companies such as Google, Facebook, and LinkedIn.

David Stodder


Barry Devlin

Faster Analytics and Better Business Intelligence

Today’s business and analytics users place high value on timeliness. Reaching decisions quickly—at the speed of thought—depends on two factors: the response speed of the data exploration tooling and the delivery speed of data into the exploration environment. Modern tools deliver these features through in-memory operation on locally stored data and direct access to operational data, respectively. The result is faster turnaround time of decisions based on more timely information.

Barry Devlin


Wayne Eckerson

Revolutionary BI: Changing the Rules of the Game

New technologies often change market dynamics, making it possible for organizations to address business needs in new and creative ways. Today, open source software, analytic databases, and other new technologies are enabling BI teams to deliver new applications that previously weren't possible in a cost-effective way.

Wayne Eckerson


Wayne Eckerson

How Pervasive BI is Good for Your Business and How to Get There

Usage rates for BI tools have nudged up from 18 percent three years ago to 24 percent today, according to TDWI Research. This abysmally low percentage accounts for most of an organization’s power users and a handful of very determined casual users. What can you do to make BI more pervasive?

Wayne Eckerson


Wayne Eckerson

Agile Analytics: The Convergence of the Cloud, Open Source and Specialized Analytic Databases

New technologies often change the rules of the game, making it possible for BI teams to address business needs in new and creative ways. BI teams that understand how to harness the power of the cloud, open source, virtualization, and high-performance analytical databases can create new opportunities to serve the business while saving money and time.

Wayne Eckerson


Back to Top

Channels by Topic

  • Agile BI »
    Includes:
    • Agile
    • Scoping
    • Principles
    • Iterations
    • Scrum
    • Testing
  • Big Data Analytics »
    Includes:
    • Advanced Analytics
    • Diverse Data Types
    • Massive Volumes
    • Real-time/Streaming
    • Hadoop
    • MapReduce
  • Business Analytics »
    Includes:
    • Advanced Analytics
    • Predictive
    • Customer
    • Spatial
    • Text Mining
    • Big Data
  • Business Intelligence »
    Includes:
    • Agile
    • In-memory
    • Search
    • Real-time
    • SaaS
    • Open source
  • BI Leadership »
    Includes:
    • Latest Trends
    • Technologies
    • Thought Leadership
  • Data Analysis and Design »
    Includes:
    • Business Requirements
    • Metrics
    • KPIs
    • Rules
    • Models
    • Dimensions
    • Testing
  • Data Management »
    Includes:
    • Data Quality
    • Integration
    • Governance
    • Profiling
    • Monitoring
    • ETL
    • CDI
    • Master Data Management
    • Analytic/Operational
  • Data Warehousing »
    Includes:
    • Platforms
    • Architectures
    • Appliances
    • Spreadmarts
    • Databases
    • Services
  • Performance Management »
    Includes:
    • Dashboards, Scorecards
    • Measures
    • Objectives
    • Compliance
    • Profitability
    • Cost Management
  • Program Management »
    Includes:
    • Leadership
    • Planning
    • Team-Building
    • Staffing
    • Scoping
    • Road Maps
    • BPM, CRM, SCM
  • Master Data Management »
    Includes:
    • Business Definitions
    • Sharing
    • Integration
    • ETL, EAI, EII
    • Replication
    • Data Governance

Sponsored Links