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Archive for July, 2011

Handy OBIEE Tricks – RR_4035 SQL Error / ORA-00911: invalid character

On my current project I am implementing OBIEE 11.1.1.5 with OBI Applications 7.9.6.3. I am running the Data Warehouse Administration Console 10.1.3.4.1 and Informatica 9.0.1 HF2 on Microsoft Windows Server 2008 R2 Standard Edition. Once I followed all of the installation and configuration steps I was able to run my first full execution plan to load my data warehouse. HUZZAH!

My spirits dimmed considerably when I ran my first incremental load and three mappings failed with the following error.

READER_1_1_1> RR_4035 SQL Error [
ORA-00911: invalid character

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EPM in the New Normal…..Slaying the Profitability Dragons in your Company….With Cost & Profitability

This is a 1 in an 8 part series to help you connect your enterprise and manage better in the new normal. 

Value of a Driver based cost and profitability solution for your EPM (Optional Webinar from July 28 on Cost & Profitability):

See below or visit SlideShare for a presentation based upon this material. This is the start of hopefully a rewarding blog series for you.

Since there are a lot of blogs out there that focus primarily on “what” (your past the what and have moved on to the how) you should be doing around EPM that you can look at in your limited and valuable time, a number of questions came to me in preparation of writing this blog series:

“How can I get your attention, to be interested in this blog and know that Perficient is the business partner I need to help me with my EPM solution?  How can I provide you with an idea that is new and fresh and is not in 500 other blogs?  How can I include value add information that provides you the answer on “how” you can enhance your EPM solution and not just the “what”?

How about this as an answer which I hope you will read and say, he knows what I deal with on a daily basis and knows how to help my company move forward:

This blog is from someone who has been in the “corporate” trenches for 25 years.  Thru trial and error has tested various methods that were “best practices” & technologies that were “state of the art” and found an optimal solution from a business and technical perspective.  From having point blank questions asked by CFO’s and then forced to find “real” solutions that makes sense.”

Perficient, Inc. (www.perficient.com),  the EPM consulting firm that I work for, can help you develop a EPM driver based cost & profitability solution that is introduced in this blog that will help you manage your business process more effectively in the short as well as the long term.

I hope at this point you are at least interested in continuing down the path with me in this blog series.  At least for one more blog.  It is written by an ex-corporate warrior for a corporate warrior in integrating cost & profitability with the financials.   You can learn from my many lessons that I learned over 25 years and build a better EPM solution for your company with cost & profitability analysis.  I GUARANTEE IT! You can move away from your Excel world madness to a world where everything is in harmony and connected…..really!  Prior to joining Perficient, I had developed components of a cost & profitability solution over a 10 year period while working for a Fortune 100 transportation company.  Cost & profitability is the same for any company in any industry.  The concept of cost and profitability and its value in enhancing the EPM process that I learned while working for a multi-billion $ transportation company works for any company in any industry.  Metrics are metrics, expenses or expenses and the link between them is the same.  Let Perficient build you a small prototype to help you visualize the solution and we will give you the EPM world.

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Posted in News

Emerging Trends in Analytics – Part I

In my previous post, I talked about organizational readiness for Pervasive BI and Advanced Analytics, and that theme briefly touched upon the new, obvious trend in BI – Analytics for the masses. As a matter of fact, some industry experts opine that “BI for the masses” has actually graciously given way to “Analytics for the masses”.  I don’t quite agree with that, although I do think that the latter is increasingly becoming a new, rather subtle trend in this space.

Even though data mining and analytics have been around for a long time; they weren’t really mainstream up until now. More and more Retail and Financial Services giants are looking to introduce their front-line folks to predictive analytics and sophisticated exploratory techniques in order to foster an “analytic-centric” culture within their organizations.  SAP BI is leading the charge in this transformation for some of our very critical clients. One of our key customers that I recently engaged with is really leveraging the complete SAP Business Objects product suite to bring about this strategic transformation in the mind-set from top to bottom.

As with any technology, success in Business Analytics is directly proportional to user adoption, and is in turn governed by user experience and interest. And, this is where we step into the larger business transformation and change management discussion, which most companies today tend to ignore. The bottom line is that organizations who use effective transformational approaches and embrace BI and Analytics as a total user experience obtain high degrees of success, whereas those who embark on this painful journey without proactively enabling the People, Process and Technology components of such change will inevitably struggle and, perhaps even fail.

Read More:

Emerging Trends in Analytics – Part II

Emerging Trends in Analytics – Part III

Emerging Trends in Analytics – Part IV

Posted in Analytics, News

SAP BI – NEW Product Names with 4.0

SAP recently announced the renaming of most of several key BI solutions and products primarily in order to bring clarity to their BI stack and ever-growing product suite. “These changes were made to make it easier for everyone to identify the SAP BusinessObjects BI solutions and better understand their capabilities. The changes will also help differentiate the enterprise-level solutions from those sold through SAP resellers, distributors and the SAP Store.”

 Former Name New Name
SAP® BusinessObjects™ Enterprise SAP® BusinessObjects™ Business Intelligence platform
SAP® BusinessObjects™Xcelsius Enterprise> Xcelsius Enterprise Interactive Viewing SAP® BusinessObjects™Dashboards> SAP BusinessObjects Dashboards Interactive Viewing
SAP® BusinessObjects™Advanced Analysis, Web EditionSAP® BusinessObjects™Advanced Analysis, Office Edition SAP® BusinessObjects™Analysis, edition for OLAPSAP® BusinessObjects™Analysis, edition for Microsoft Office
SAP® BusinessObjects™Web Intelligence SAP® BusinessObjects™Web Intelligence (Installer name and documentation refers to “Interactive Analysis”)
Crystal Reports SAP® Crystal Reports

 

OBIEE 11.1.1.5 Project Log, Part 1: Operating Systems

Welcome to my Oracle BI 11.1.1.5 Project Log series. This will be an open ended series related to decisions made and lessons learned in a live Perficient project. I will be focusing on the technology questions which should be generic to any OBIEE implementation.

Which Operating System Should We Use?

If a client has a strong preference for a particular operating system this question is a simple matter of confirming which version of the desired operating system is certified with the version of OBIEE 11g. Sometimes, however, a client will ask a frighteningly simple question, “What operating system do you recommend we use?” This simple question, while demonstrating a great deal of trust, also puts quite a burden on a consultant to weigh all of the options.

The Oracle Business Intelligence Suite Enterprise Edition 11g Release 1 Certification Matrix spreadsheet is the definitive guide to the platform options available, but it does little to explain the benefits and disadvantages for each. I will be pointing out the decisions made on my project and what I learned about the impacts of these decisions. It may perhaps go without saying, but be sure to confirm you are using the latest version of the Certification Matrix before proceeding with your hardware and software purchases.
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Managing BI Performance Problems Series Part 2: Indexing

When it comes to performance problems indexing is the bread and butter of most data warehouse developers. And why not? It’s a cheap and easy way address simple performance problems. However, like anything cheap and easy it can only fix the cheap and easy problems. Indexing will not solve large underlying performance problems, but it is a good way to get the “low hanging fruit”. Below are some basic tips on effective index use.

Keep in mind, too many indexes is a bad thing.

Indexes not only take up a lot of space,  indexing too much data will actually make your database slower. The general rule of,  “When all data is crucially important data, then no data is crucially important.” tends to hold true here. This doesn’t mean one should shy from using indexes. But one should take care not to over index. Every index should be in there for a reason and a good one.

Explain plans are your friend!

Developers often think they can solve a performance problem just by looking at a SQL statement and throwing indexes whereever they like. At the very least, an explain plan should be run because it will show where the problems are likely to lie and bring to light possibilities that a simple glance at the SQL might have missed.

Think ahead functionally in creating indexes

A performance problem might point to one particular column. Indexing the singular column and moving on would be simple. But if you know that users that query on that column tend to also filter on another column it might make sense to create a multi-column index instead of just taking care of the singular column. Again, use your best judgement to not create a index that will hurt you instead of help you. Having a functional knowledge of how users are coming at the data can help in creating a holistic  indexing solution.

Recognize your weapons. Practice them well.

Some companies shoot themselves in the foot by using the wrong index type in the wrong scenarios. Others try to fix all problems with just one kind of index. Knowing which index to use is just as important as knowing when to use one. There are many different ways of building indexes so it is important to know what to use and when. Does the column you’re looking at have a high cardinality (like Customer Name, Product Name, etc)?  If so, then a “normal” or btree index would be best. Do you want it clustered or not? Is the data low cardinality (such as gender, job title, end market segment)? If so, Then a bitmap indexes tend to be best.

Also keep in mind some database products allow for different kinds of indexes. Work with your DBA (remember Part 1 of this series?) to find the right index type for the performance problem.

CFOs, It’s Time to Increase Visibility Into Financials

Mastering your company's finances requires reliable and comprehensive business intelligence

Try asking the following questions about your company:

  • Are we using analytics?
  • Do we share the same data across the company?
  • Are we measuring the right things?
  • Do we really have a handle on cost?
  • Do we strategize from the top or rationalize from the bottom?
  • Are we moving the corporation forward or watching from the sidelines?
You want your company to be considered productive and adaptive to change. You and your company’s leaders deserve comprehensive, instant, reliable and insightful visibility into the organization’s finances in order to ensure this.

 

If you’re struggling with any of the above questions, now is the time to take a deeper look and learn about a driver-based cost and profitability model for Enterprise Performance Management.

 

On Thursday, July 29th, Perficient will host a free webinar at 12:00 CST, specifically geared toward finance executives.
Register here

 

Along with the launch of our business intelligence blog here, gain access to our BI and EPM experts starting with this webinar, and subscribe to email alerts from this blog in the top right corner of this page.

Posted in News

Organizational Readiness for Advanced Analytics

Continuing on my theme of big data, it is evident that sophisticated, real-time, “appliance-focused” analytics is gradually taking over the Business Intelligence debate. Last week, while meeting some key Executives at a critical manufacturing client, it was apparent that large Manufacturing, Retail and Financial organizations are laying more and more emphasis on “analysis-oriented” BI rather than just being “reporting-centric”. The shift is almost stark, and lends a futuristic, analysis-driven perspective to their BI conversations. However, are these giants really ready for the cultural and organizational challenges that such a perspective poses? Are their leaders and grassroots workers ready to embrace this shift in business thinking?

I strongly advocate that such visionary corporations invest more into ensuring their overall organizational readiness for definite strategic BI advantage. By simply purchasing and deploying a slew of predictive analytics and visualization technologies without much thought to long-term business consequences, companies may unintentionally leave out erecting those vital bridges between vision and strategy, people and technology, and execution and success! And that is why, when thinking of large-scale business transformation programs, my focus is always on bringing about that much-needed mind-set shift at all levels of the organization, in order for BI and Big Data projects to be successful.

Therefore, aligning your long-term strategic business vision with your BI strategy, and comparing your BI maturity and BI strategy with others in the market, will be the first steps to understanding if your organization is ready for that “analytic” perspective.

Posted in Analytics, News

Customer-Centric Business Intelligence: Predicting the Future

Faster analysis and decision making can create a powerful strategic advantage.  Enterprise Performance Management (EPM) can be used as a powerful diagnostic tool through the use of automated scorecards and dashboards.  A company can identify potential flaws and short-comings in the cause-and-effect relationships that drive company performance.  Reaction times can be cut from hours and days down to minutes.  As the balanced scorecard is used and feedback is received, a company can begin to test the hypothesis of their original strategy through formal testing, such as statistical regression analysis.  EPM, through Business Intelligence reporting tools, provides a powerful platform for this activity.

EPM can also predict future behavior by linking past financial performance to a simulated future performance. Essentially, managers can view the company’s pro forma income statement by customer segment and profit center to evaluate future trends. These pro-forma income statements can calculate sales per customer, cost of goods sold as a percent of sales, acquisition costs per customer, marketing and operations costs per customer, and projected changes in these measures over time.  Past financial information can be used as a “base case” to validate the information provided in the pro forma statements. 

The Ever-Evolving Customer Relationship

This base case can then be used to compare against projected marketing investment allocations to determine worthwhile future investment or necessary changes in strategy.  Time trend analysis should show customer attrition levels decreasing among the most profitable customers and movement of less profitable customers to more profitable products or less costly distribution channels, which will further drive profits to the bottom line.  Valuable information gleaned from this analysis can be incorporated into the next Strategize process in the closed loop EPM system.

Successful companies realize that strategy is an effective way to grow with market conditions.  Strategy is most effective when it can evolve with the competitive landscape, economic conditions, changing customer data, and correlations found in every business environment.  Most of these same companies utilize the balanced scorecard methodology to meet these objectives.  Overall, EPM provides the balanced scorecard approach with a nimbleness that it does not have on its own merit.  Traditionally, users of the balanced scorecard approach revise their strategy map on a yearly, or perhaps quarterly, basis, which may or may not be adequate given business conditions.  Using EPM, the strategy map can be tested, supplemented, and cascaded down throughout the company efficiently to drive firm value through important customer relationships.  Using this Business Intelligence enabled strategy platform to communicate and evaluate employee performance will provide a powerful catalyst for company growth.

Emerging Data Innovations

This is unmistakably the world of the “data scientist” and the “analytics guru”!

As growth of data outpaces our ability to process and even understand it in its totality, newer technologies and roles are emerging for handling the challenges posed by “big data”.  More and more Retail, Financial, Insurance and Social media giants are treating data and business analytics as a computational science. More and more emphasis is on “in-memory” applications, private and public data clouds, and lots of innovation around big data and low-latency, real-time analytics.

For instance, consider these emerging BI scenarios:

  • Retailers are increasingly focusing on “just-in-time” Business Intelligence.
  • Huge numbers of corporations use Big Data technologies such as Hadoop and cloud computing to analyze massive amounts of application and transactional data.
  • Emergence of public and private data cloud start-ups capable of handling petascale problems is defining the new BI world.
  • It is amazing how data growth these days is being talked about more and more in terms of Petabytes, Exabytes, and Geopbytes!

Tremendous scale of innovation is taking place around next generation DW, in-memory analytics, and cloud computing. Therefore, if you have not heard of these new technologies – Data Appliances (SAP HANA), Hadoop, Cloud Databases– then it’s time to play catch-up. These all represent the next Generation in Data and Business Intelligence!

Some of the increasingly popular names in the Big Data space are:

SAP HANA: “This data appliance enables organizations to analyze business operations – based on large volumes of transactional and analytical data – and to instantly explore and analyze the data from virtually any data source in real time.” Data is primarily captured “in memory” as business unfolds, and flexible views expose analytic information rapidly.

Hadoop: Designed to process terabytes and even petabytes of unstructured and structured data. It breaks large workloads into smaller data blocks that are distributed across a cluster of commodity hardware for faster processing.   

Columnar Databases: Columnar querying brings about performance efficiencies, and is unmatched by any row-oriented DB.

The companies to watch out for in this space are SAP, HP, Teradata, IBM, Splunk and Nothscale, just to name a few.

Posted in News