Business Intelligence

Self-service BI is a very popular topic these days. It is beneficial to the IT staff developing the BI environment – they are freed up to do more value-added activities. It is quite useful for technologically savvy business analysts or data scientists – they could begin producing their own analytical results.

As the velocity of business increases, business users are less willing to wait for the IT department to create custom reports and analytics. Many users now expect to be able to interact with information and create their own views of data to address pressing business issues.

Big data is growing fast as organizations devote technology resources to tapping the terabytes (if not petabytes) of data flowing into their organizations and externally in social media data and other sources.

Apple defined a new category of computing with the release of the Apple iPad. It also reinvigorated the BI market with sexy dashboards on every tablet. BI on mobile devices promises to make BI more immediate and accessible for executives and field workers alike.

The diversity of data formats presents new challenges for gaining a complete and accurate view of information across the enterprise. Successful organizations are governing “big data” at the entry point (within an application, Web logs, documents etc.)

Customers today are more than just customers. Using social media networking, they influence others and reveal their buying interests in products and services. Organizations know that to compete effectively, they must capture as much information as they can about customers and analyze it effectively to discover patterns, trends, and other vital clues. Social media networking activity is generating big data – and these growing sources are the new frontier for customer intelligence.

Most organizations have BI mavericks in their business ranks. These are the folks who use analytics a lot but are very frustrated with the BI environments provided by their IT counterparts. They never seem to have the data they want - or the way they want it - so they go rogue and acquire or build out their own solutions, ignoring the value that enterprise BI can provide.

Data discovery is one of the hottest categories in the BI market today, allowing business users to explore data visually, with minimal IT support or extensive data modeling. As the variety of data explodes, decision-makers want to combine data from the data warehouse with unstructured content such as customer comments, resumes, tweets, and blogs.

Many companies have self-service BI as their vision for empowering users. But empowerment can come at the price of overwhelming business users accustomed to receiving only a fixed report.

The business intelligence tools market continues to bring innovations that have made BI more engaging, insightful, to an increasingly broad spectrum of users. This webinar briefly describes some of the hottest trends such with an emphasis on In-memory, mobile BI, and social BI.

Early adopters used business intelligence for operational reporting or analyses that guided strategic decision-making, supporting senior managers but largely ignoring the hundreds, if not thousands of decision-making opportunities presented each day.

Companies in every industry operate in relation to a continuous sequence of many events – products are manufactured, sales are made, inventory is tracked, or packages are shipped. While there is no need to be notified when events happen as planned, when anomalies occur (such as a snow storm that prevents delivery), the organizations that receive early notification have an advantage over those that do not.

A picture can paint a thousand numbers and broaden the appeal of BI tools. Specialty BI vendors are growing at a rapid pace and visual discovery has become a critical component of the BI platform.

Business intelligence (BI) applications are playing an ever increasing and important role in driving and optimizing daily business operations. This trend is leading to major changes in both the functionality and the usability of BI-related technologies and products

How can the principles of branding be applied to BI to help multiple groups in large organizations work collaboratively across departmental boundaries?

How can the principles of branding be applied to BI to help multiple groups in large organizations work collaboratively across departmental boundaries?

The Leicester Tigers rugby team uses predictive analytics to leverage data about the physical condition of its players in order to prevent injuries and enhance performance. - By Samuel Greengard The list of uses for predictive analytics seems to expand daily. Businesses and government are applying it in areas as diverse as health care, customer retention, energy conservation and crime prediction. Although sports organizations have tapped analytics for years the book ...

This paper, written by David Loshin of Knowledge Integrity, Inc., highlights some of the most common myths about data quality management and guides the reader in developing an effective DQM strategy.

This paper, written by David Loshin of Knowledge Integrity, Inc., highlights some of the most common myths about data quality management and guides the reader in developing an effective DQM strategy.

Data modeling is often seen as a technical activity, indistinguishable from database design. However, with the right perspective and techniques, data models are extremely useful to other stakeholders.