Business Intelligence Evolves to Serve Users

bi_bigdata
Business data and BI software are currently beginning a new phase of evolution. In this new phase, users of business data will be able to collaborate and connect with other colleagues and team members without multiple spreadsheets and laborious processes.

The BI user experiences of past decades are being re-thought and fast collaboration and crossover functionality are the way of the future.  Southard Jones, in the May 9th Venture Beat article Blurred lines: Reimagining the user experience for business intelligence, details how companies are developing new ways of delivering business data and what companies will be looking for in the future.

The article is of interest because it discusses that the business intelligence space needs to evolve to meet the needs of modern businesses.  Currently, there is little crossover functionality between products, and products are rigidly aligned to arbitrary user “roles” like information consumers vs. producers. But, people are not rigidly defined in their roles; they need to be able to answer questions quickly, using their business data. “Blurring” the line between consumers and producers of information is one example of how business intelligence products need to evolve, because blurring that line will make everyone more productive.

Crossover functionality is another topic this article broaches. To quote Jones, “Ensuring success with BI and analytics also means recognizing that different people prefer different tools.”  We whole heartedly agree! People in business should be able to access relevant, informative data quickly, and from whichever tool seems appropriate to them.

His article feels very validating because at least someone in the BI industry sees the status quo is no way to continue.  Jones also writes, “The modern business landscape demands a new approach to the user experience. […] And one that allows interoperability between different products. Our work styles have evolved. BI and analytics should do the same.”

One such software, developed by PARIS Technologies, is taking on this new, modern business crossover and collaboration and use of multiple products with their newest product Olation®. With this kind of technology, companies can eliminate inaccurate data and time-consuming processes that stem from data located in various applications, spreadsheets and databases.  With Olation, data is centralized in a non-proprietary database and access to that information is permitted simultaneously by multiple users in their different applications.  It’s is a game-changer, especially if you’ve been struggling with a typical or limited BI tool. With everyone in the business working from the same source data set, and Olation’s calculation engine doing the formula and calculation work, there is little manual spreadsheet work to be done. Which means analysts can actually answer questions quickly and spend time getting to the meat of data discovery.

Learn More About Olation

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Fast Data: How to Gain Insights from Big Data

fastData

In this Forbes.com article, Making Big Data Fast, Howard Baldwin makes a great point about data needing to be FAST in order to deliver value.  Big data has a historical focus, whereas Fast Data seeks to enable action.  For us at OLAP.com, we have seen “fast” as an important qualifier since the early definition of OLAP—FASMI, or Fast Analysis of Shared Multidimensional Information. Baldwin emphasizes the increasing importance of moving at the velocity of data; being empowered to gain insights from data, and; being able to react immediately with an action or other response. We couldn’t agree more with his stance, and kudos to him for drawing attention to it.  It will be increasingly important in 2015.

We also love the “I Love Lucy” reference at the beginning of the article.  The sponsors of OLAP.com, PARIS Technologies, are long-time experts at super fast data delivered for actionable insights.  Explore our website.

Is HTAP the latest type of OLAP?

HTAP OLAP hybrid transactional systems

Some vendors have run from the four letters OLAP…and yet, articles continue to be published, and assertions made, that “analytical processing” is entering a new phase. There’s a new acronym in the market, HTAP, which stands for Hybrid Transactional/Analytical Processing. Given the close similarity (two out of four words ain’t bad—and it’s three if we consider the once-upon-a-time category HOLAP), is there a difference? This post from one of our favorite bloggers, Timo Elliott, may help you decide…

What is HTAP?

Read more about PARIS’ take on the HTAP technology on the PARIS Tech Blog






Infographic: Why BI is Key for Competitive Advantage

A great infograhic from the Master of Science in Computer Information Systems program at Boston University.  The BU researchers focused on: growth of business intelligence, management of data, decision-making and budgeting.  Enjoy!

 

BU-BusinessIntelligence-Is-Key

{Originally posted here}

Excel-Friendly BI Helps Teach Business Analytics at the University

By Bill Tastle, our newest OLAP.com contributor

As a Professor at an AACSB accredited business school, I am responsible for preparing  business students who are eager to enter the marketplace upon graduation. Naturally,  I spend a lot of time researching about what skills will best serve them. This can be more of a challenge than one might think because today’s skills may not be in demand tomorrow but one thing appears to be quite apparent; the need for graduates trained in the methods of business analytics will be in demand for at least the next decade.  Thus, my business school faculty members and I have been discussing how best to incorporate Business Intelligence (BI) skills into our existing program.

This is a bit exasperating if one’s business school/college is AACSB accredited, because the required set of courses that comprise the curricula have very little room for extras.  BI, I must argue, is not an “extra” but rather, a critical component to a student’s undergraduate business education.

So, I carefully examined the landscape for suitable software tools to bring into my undergraduate classroom environment. I spent considerable time reading everything I could find from many, many companies and multinational corporations hawking tools for BI. Eventually, I happened upon a company featuring a strong “Excel user-friendly” product.

There seemed to be a natural logic to doing BI in Excel, given the pervasive use of spreadsheets in the business community, but what I had discovered is that many software vendors try to address the Excel “problem” by doing away with Excel altogether.

This company had a different approach, which is to embrace what Excel has to offer as a familiar front end. I sent off an email asking for information and virtually immediately was in contact with someone at the company and quickly received their literature. I read it!  Carefully!  The more I read, the more excited I became.

It is pretty obvious that all business schools teach Microsoft Excel, some at a trivial level, which is little more than a superficial introduction, and others are more advanced levels.  Perhaps I am a statistical outlier, but at my school, sophomores must become Microsoft Expert certified to pass their required business technology course.

So, the ability to bring a BI tool directly into Excel in the form of a simple add-in has made all the difference in the world.  Students receive an introduction to the world of BI and quickly discover what is meant by “multi-dimensionality,” an important concept when business performance models (“cubes” in BI terminology) are being constructed.

I could not do as good of a job teaching Business Analytics if I had to teach an enterprise database program first, just to get to their dashboard graphs.  Furthermore, being able to attach the BI software program to other sources of data made it all the more fascinating to students who are amazed to discover they can access data not only from other worksheets, but also from database tables.  This is also a fantastic achievement, getting data from multiple sources with different data structures.

I am about as pleased as can be. In fact, I am offering an additional course in BI and I have other courses undergoing development.  The pedagogy involved in the skills of Business Intelligence is being written in this decade, and the benefit of using an “Excel-friendly” tool in the classroom brings daylight to the mysterious area of “intelligence gathering” and how it is used in decision-making solutions.  For me, it is particularly exciting because it is the beginning of a thrilling direction in business education.

Next time:  Analytics in the Business Dean’s Office

 

2 Questions to Ask about Your BI Project

Two questions to ask about your BI project

If you are considering a Business Intelligence Project, there are two questions you should consider.  These questions will help you pinpoint what exactly you may need to do with your BI project, as opposed to simply getting “analytics” or “implementing a BI tool”.  Anyone who has experience in the BI market knows that the nature of  these projects can be deep and involved, and it helps to have a clear idea of what you are trying to accomplish.

From that article, “Two Questions That Will Dictate the nature of your Business Intelligence Project” on  DashboardInsight.com, the first question is, can we discover significant relationships in our data that aren’t apparent without elaborate data mining techniques? The example the article presents is of Target’s uncanny ability to recognize a women who is in her second trimester of pregnancy–an ideal time to become the object of a woman’s buying habits, and and ideal time to ship out some coupons! This would be a significant relationship that is hidden in the data — a change in the type of lotion or the purchase of a large bag. Targets ability to, ahem, target this change in a woman’s life wins them a customer for life and big bucks in the long term. [Read more about Target and pregnancy marketing here]

The second question is about accuracy– can you improve on a common, repeated action to improve customer retention, marketing efforts, or predict customer behavior? This type of project usually involves looking at large amounts of historical data to see what is to be learned in order to avoid making the same mistakes again.  As markets become over-saturated, the retention of customers is very important, if not crucial, and this type of BI project improves customer service and marketing efforts to large effect.

Read the full article from Dashboard Insight: “Two Questions that will Dictate the Nature of Your Business Intelligence Project”