Olympic Analysis Using Pentaho

July 30, 2012

In honor of the Olympics…here is an Analytical Dashboard I created to compare and contrast the medaling countries from 1976 to 2008. Enjoy.

Wayne Johnson
Senior Sales Engineer

This blog was originally posted Wayne’s blog, Business Intelligence in Real Life


Pentaho update to BBBT

July 24, 2012

Pentaho had the privilege of briefing the Boulder BI Brain Trust (BBBT) on July 20, 2012. The Boulder BI Brain Trust is a gathering of leading BI analysts, experts, and practitioners who attend half-day presentations from interesting and innovative BI vendors. After a very interactive morning presenting to the group, Pentaho CEO, Quentin Gallivan and SVP of Products, Jake Cornelius sat down with Claudia Imhoff, president and founder of the BBBT to discuss some of her questions from the morning about Pentaho.

The result is an excellent update about Pentaho products, technology and overall direction. Listen to a podcast of this interview to learn the following about Pentaho:

  • How Pentaho is differentiated?
  • What are the market forces for business analytics and how are they converging?
  • How is Pentaho meeting changes in market?
  • Overview of the Pentaho platform
  • What’s the reason for the BI embedded analytics trend?
  • What are some Pentaho big data customer examples?
  • What’s in the near future for Pentaho and its products?

Listen now: Claudia Imhoff interview with Pentaho leaders Quentin Gallivan, CEO and Jake Cornelius, SVP of Products


Is Your Big Data Hot or Not?

July 23, 2012

Data is the most strategic asset for any business. However, massive volumes and variety of data has made catching it at the right time and right place, discovering what’s hot – and needs more attention – and what’s not, a bit trickier these days.

 Heat grids are ideal for seeing a range of values in data as they provide a gradient scale, showing a change in data intensity through the use of colors. For example, you can see what’s hot in red and what’s normal in green; and everything else in various shades of color in between. Let me give you two examples of how companies have used heat grids to see if their data is hot or not:

Example #1 – A retailer is looking at week-by-week sales of a new fashion line to understand how each product line is performing as items get continually discounted throughout the season. Data is gathered from thousands of stores across the country and then entered into a heat grid graph that includes:

  • X axis – week 1 through 12, beginning from the launch of a new campaign (e.g. Nordstrom’s Summer Looks)
  • Y axis – product line (e.g. shoes, dresses, skirts, tops, accessories)
  • Color of the squares – % of discount (e.g. dark red = 70%, red = 60%, orange = 50%, yellow = 30%, green = full price)
  • Size of the squares – # of units sold

Looking at this graph, the retailer can easily see that most shoes sell at the beginning of the season – even without heavy discounts. This helps the retailer predict inventory levels to keep up with the demand for shoes.

It also shows that accessories almost never sell at regular prices, nor do they sell well when the discount levels are higher than 70%. Knowing this, the retailer can control its capital spending by not overstocking on this item. The retailer can also increase profit per square footage of their store by reselling its accessories earlier in the season to avoid high markdowns and inventory overstocks at the end of the season.

Example # 2 – A digital music streaming service provider is using analytics to assess the performance of its sales channels (direct vs. sales through different social media sites such as Facebook and Twitter) to guide future marketing and development spend. For that, the company uses a heat grid to map out:

  • X axis – various devices (iPhone, iPad, Android Smartphone, Android Tablet, Blackberry)
  • Y axis – various channels (direct site, Facebook, Twitter, …)
  • Color of the circles – # of downloads (0-100 = red, 100-1000=orange, 1000-10000 = yellow, 10000+ = green)
  • Size of the circles – app usage hours per day – the bigger the size, the more usage

This graph helps the music service provider analyze data from millions of records to quickly understand the popularity and usage patterns of their application on different devices, sold through different channels.

Heat grids can be use in variety of other forms, such as survey scales, product rating analysis, customer satisfaction studies, risk analysis and more. Are you are ready to find out whether your big data is hot or not? Check out this 3 minute video to learn how heat grids can help you.

Understanding buyers/users and their behavior is helping many companies including ideeli – one of the most popular online retailers – and Travian Games – top German MMO (massively multiplayer online) game publisher – gain better insight from their hottest asset – their big data!

What is your hottest business asset?

- Farnaz Erfan, Product Marketing, Pentaho

This post originally appeared on Smart Data Collective on July 13,2012


Words of Wisdom

July 20, 2012

We are very lucky to have some words of wisdom today from The Most Interesting Man in the World.

Stay integrated my friends!


Welcome Pentaho’s newest board member, Brian Stevens

July 17, 2012

As Pentaho continues to rapidly grow it is important for us to add advisors who can offer guidance in core areas importance. To that note, I am excited to announce that Brian Stevens, CTO and vice president, worldwide engineering, Red Hat, Inc. has joined the Pentaho Board of Directors.

Brian brings tremendous experience in cloud computing and software innovation to Pentaho at a time when the business analytics market is being transformed by a deluge of large and diverse data volumes, the mainstream adoption of cloud solutions, and need for interactive analysis.

Brian’s insights into the ever-changing software landscape will be invaluable as we continue to innovate the Pentaho Business Analytics platform with its unified business analytics, data integration and big data capabilities to meet the demands of big and disparate data environments.

Quentin


What happens with Pentaho, Infobright and Semphonic team up…

July 16, 2012

The challenge with organizations’ Web analytics efforts is finding a way to meaningfully represent digital behavior at the customer-level.  Pentaho and our big data partners, Semphonic and Infobright, came together to address this challenge and turn websites into revenue generating machines.

Great results happen when you bring together great technology and expertise. The three of us have created a customizable framework for Web analysis and digital measurement. CMO’s, product managers or marketing analysts can rapidly answer questions regarding Website usage, customer behavior, marketing effectiveness and site performance and quickly uncover meaningful insights from big data Web analytics.

Want to learn more?  Take a look at the resources we’ve put together to get started with Pentaho and big data web analytics:

Donna Prlich
Director, Product Marketing
Pentaho


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