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Ryan Johnson

Ryan Johnson is a lead consultant specializing in Business Intelligence and Data Warehousing as part of the IBM Business Analytics group. He has extensive education in the area with a master of science in business intelligence and specialized training to accompany his many successful client engagements.

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Solution-Focused Product Sales and …Football?

In the after glow of the suspect lighting at the Super Bowl, I’d like to present an analogy of solution-focused product sales in business analytics to the game of football. Before I tackle the analogy, let’s first huddle-up and discuss the X’s and O’s of solution-focused sales delivery.

Solution SalesLong gone are the good old days of car salesman tactics where it was more about convincing to buy than guiding to an educated decision. The ability for customers to research anything is a mouse click away, but context of a product in their business is hard to find. This is where solution sales for business analytics products becomes an effective method of communicating value to customers today. This includes using a defined business need or question as the reference point to demonstrate the product capabilities. By educating the customer through a practical example, both the product and team capabilities are indirectly highlighted.

When looking to the game of football, there are common elements with solution sales. Additionally, objectives for each role in football can help explain the objectives for each role in solution sales. Here is the rundown:
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Business Intelligence Buzzwords: Taking the Good With the Bad

One of the most important aspects in the progression of business intelligence is the use of buzzwords. These words drive interest in the field and provide common language between the world of technology and business to steer initiatives. However, in an ever-changing industry it is difficult to pinpoint standard definitions. Buzzwords often overextend their original meanings and often blur lines between other buzzwords. So how do you manage to keep up?

One good way to create some barrier on definitions is to compare several definitions from various experienced professionals. A good of example of this is BI Buzzword Breakdown | 5 Experts Tackle 3 Business Intelligence Definitions by Michael Koploy. An additional approach is to actually compare the application of different buzzwords side-by-side as seen in this graphic from (SOME) TRUTH ABOUT BIG DATA:

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From Decision Management to Predictive Analytics: IBM SPSS

IBM SPSS has been getting a lot of attention lately due to increasing interest in buzz words such as big data, predictive analytics, data mining and statistical analysis. Additionally, the latest version of SPSS Statistics (version 21.0) was also released this month. But what is SPSS and how does it fit within the current solutions offered by IBM? While SPSS was announced as an acquisition by IBM in July of 2009, version 1.0 was released in 1968 as statistical software for social sciences. Since then, SPSS has maintained its foothold as a premier statistics tool while also expanding into other add-ons and complimentary applications. While SPSS Statistics has been the foundational tool, the complete family is made up of four components:

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Google makes BI push with Cloud Platform Partner Program

One of the more notable announcements in the last month was that of Google’s Cloud Platform Partner Program. The platform currently offers Google Compute Engine, Google App Engine, Google BigQuery, and Google Cloud Storage. The partner program is designed to extend the use of these applications by allowing integration of other
Technology Partner applications as well as expanding implementation options with Service Partners. In an earlier blog post, IBM CEO Study: Leading Through Connections, we looked at the idea of amplifying innovation with partnerships. Google has certainly positioned themselves to embrace this mentality throughout several cloud-based fields with this move. However, we will focus on the moves within the business intelligence space, particularly around Google’s BigQuery application.  Here are the highlights of the eight partnerships announced with some details on the objective of each:

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Make the Best of Current BI First

A recent article on Computerworld.com, “15 tips on how to get more from Business Intelligence data,” brings up a great perspective when looking at Business Intelligence initiatives. While the popular topics of  big data and self-service BI may resemble the shiny new mountain bike in the window, what sort of polishing can you do to the Schwinn in the back of your garage? To often BI reporting and initiatives are implemented in a way that puts the focus on the wrong aspects. Poor usability and over-complex visualizations plague BI reports across all industries. As a result, the user is unsatisfied, current adoption falters and future BI endeavors become a challenge to get approved. Through the changes in business needs and technology advances, BI will continue to be looked at as a program rather than a  project.  To assist the continual cycle of bringing in new products to meet new business challenges, these are some opportunities to explore:

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“What is MDM?” – Video Overviews

Today we are going to look at a widely used acronym in business intelligence called MDM, or Master Data Management. Sure you have heard it before, but it is often tossed in with a series of other acronyms without much context. So what is MDM in a practical context?

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Financial Services Sees Big Value In Big Data: Top 10 Trends

SunGard has identified ten primary trends that have been shaping the financial services industry’s use of big data in 2012. These trends cover wide-ranging drivers such as predictive analytics, compliance, mobile and globalization. To accompany the list, Neil Palmer and Michael Versace (global research director at IDC Financial Insights) discuss these trends in more detail via webcast. Below is SunGard’s list of the key 2012 trends that are shaping big data:

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Call from Forrester for (un)balanced BI approach

A recent Forrester Research report loosely applies the 80/20 rule to a company’s BI environment. In this case, 80% of BI requests should be handled by users themselves while 20% should be handled by the IT-driven, enterprise-wide applications. This is a heavy swing that encourages the influx of self-service BI platforms. The primary reason for this shift is the growing demand for BI and the backlog these requests cause for IT. Forrester believes this is caused by these bottlenecks:

  • BI requirements change faster than an IT-centric support model can keep up
  • Conventional waterfall SDLC approaches are poorly suited for BI
  • Business and IT do not always see eye to eye on BI applications and projects

There is also an evolution in self-service BI experience. What was once imagined to be a drag-and-drop, point-and-click interaction has now shifted to subtle replication of the interfaces of Google and Facebook. The intent is that a “user-friendly” approach should be designed using interfaces users are already trained in and comfortable with. In the recent Forrester Wave “Self-Service BI Platforms, Q2 2012,” report, these were the primary capabilities evaluated:

  • Auto-modeling of raw data
  • Ability to create calculated measures and metrics on the fly
  • Collaboration between business users and IT staff
  • Data virtualization and drill anywhere
  • Prompting for columns at runtime
  • Search-like GUI
  • Application sandboxes
  • Write back for “what if” analysis
  • Exploration and discovery on raw, unmodeled data
  • Optional semantic layer
  • Migration of self-serviced BI app to production

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Zoho CRM Adds Business Intelligence Reporting

ZOHO Corp. is  best known for its Zoho suite of on-line business applications. The company was founded in 1996 and  has been growing its offering of products since.  While the Zoho CRM application has been in its latest version since last December, Zoho is now adding business intelligence reporting and analytics. This will include over 70 pre-built reports and dashboards with the ability to customize as well.

As software-as-a-service has become more popular we have seen an increasing number of new entrants in the business intelligence space.  With less barriers of entry for both the company and the consumer by using the cloud, there is no reason to think this will stop any time soon.

To test out the new features for yourself, check out the public demo database. Otherwise, see the demo video below:

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Teradata Talks Enterprise Data Integration

Teradata has been long been known for its powerful data systems and drive to push benchmarks for large data volumes. In fact, in 1992 Teradata built a first of its kind system for Wal-Mart, capable of  handling 1 terabyte of data. One of the main advantages to routinely working with very large data sizes is the exposure to integration, data quality (DQ) and master data management (MDM) techniques. From the experience derived after years of this type of work, Teradata has found themselves in a position as experts on the topics. With that, here is a video that includes these buzzwords and more as Teradata describes how to achieve data integration at the enterprise level: