Tag Archives: Business Intelligence

99-Spreadsheet modeling, Excel power users, Excel resources

Introducing…. Power Pivot (with Excel)

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I think everyone can agree that pivot tables are great excel tools which make analyzing and sorting massive amounts of data a life saver. However, over the course of the past couple years I have been introduced to Power Pivot. Yes, Power Pivot. Pivot tables on steroids. At first, I was pretty intimidated because of the sheer size and complexity on the surface. But after spending some time learning and taking “lunch n’ learn” course at work, Power Pivots and I are becoming friends. My favorite part is being able to run pivot tables essentially off other pivot tables. At work, we’ve also created many tools that allow our leaders to simply and easily run their own reports for specific requests, which saves everyone time. (The analyst teams refresh the data regularly as needed).

I’ve included a couple links below about Power Pivot, and would encourage all to consider using the valuable tool the next time you are looking to crush some colossal data. It’s available as a free add-on for Excel 2010 and now comes standard on Excel 2013.

Happy Pivot Tabling!

 

WJEM

 

https://www.youtube.com/watch?v=URy_uQYS49s

http://info.110consulting.com/blog/bid/374825/Top-10-Benefits-of-Using-Excel-PowerPivot

http://blogs.office.com/2010/10/01/top-5-ways-powerpivot-helps-excel-pros/

05-Creating & constructing good solutions, 99-Applying business intelligence, business databases, creativity methods

Bridging the Gaps for Future Mobile BI Users

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Most of us utilize Business Intelligence software mainly on our laptops, but the world has started to drift towards the mobile trends. Many workers travel and rely on tablets or phones for presentation aides yet there are still gaps between the corporate data and these mobile devices. Below are some examples;

Culture Gaps

  • Fast Data vs. BI Reporting
  • Friendly Users
  • Post PC Diversity

Technology Gaps

  • Cloud Platforms
  • Social Interaction
  • All Encompassing Ecosystem

The 2 articles in the embedded links below, focus on the current gaps that we see today between the mobile world and business intelligence in terms of culture and technology. Hopefully in the near future we can bridge the gaps and truly rely on the cloud and other internet services to tailor to our business needs.

05-Creating & constructing good solutions, 99-Applying business intelligence, business databases, creativity methods

The ‘Right’ Strategy For Business Intelligence?

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Companies often look for templates or real world examples when it is time to bring a business intelligence system online. While they try to mimic a company similar to theirs, each organization is faced with their own respective needs and challenges. One commonality does exist in most roll outs as the strategy standard; involving end users and thinking big but starting small. This article discusses the best implementation strategy that is shared among companies.

Involving the users allows there to be early buy in from many members of the organization and it promotes the benefits immediately.  With many ideas flowing about, the implementation team is well prepared to deliver the best system. Additionally, pilot programs to test this system in are critical. Mass roll outs without the proper testing can lead to various issues and each department usually has its own pace to adopt these technologies.

Timelines allow for organized planning but its really the end user acclimating to the new system and providing feedback which will determine how long this implementation can take.  Does anyone have any other advice that may complement this over arching advice?

05-Creating & constructing good solutions, 99-Applying business intelligence, business databases

Data’s Credibility Problem for Business Intelligence Users

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Data driven decisions are the basis of finding solutions that will solve any problem. Utilizing the BI tools are an everyday affair for me, which can often have repercussions should the information be inaccurate. Before we can apply BI to decision making, there is a need to analyze and ensure the integrity of the data.

HBR had a good article regarding the time lost due to looking, identifying and correcting errors in data sets. Time is of essence when it comes to project deadlines and there is nothing I rather not do, than waste time. Companies need to meet deadlines and they give there full trust in data sets. If an error comes up at the last minute when conducting analysis, we often look to quickly fix the data set without fully addressing the root causes.

Previously working in the retail clothing environment, many issues would come up regarding data integrity of our systems. Much of the blame would come back to the IT team and they would try to fix it themselves without going to the respective department who owned the data set. Not only is this inefficient but does not encourage collaboration and communication.

The solutions to this issue is better communication between the data creators and users. Too often do we put a band aid on a mistake and never go to the source. The focus should be shifting the responsibility from the IT team to the managers of data sets. This article gives examples at Chevron and the processes we should be implementing to ensure the right decisions are made with the right information.

I invite others to see if they have utilized these techniques in their companies through their management. What works best for your teams when these issues arise?