Connect – a Simba Technologies Blog

Excel 2007 and SAP HANA - a how to document

We just published a how to document for Connecting Excel 2007 directly to SAP HANA.  If you use or are evaluating SAP HANA, this is a must read.  If you are interested in connecting Excel 2003 or Excel 2010 to SAP HANA, give me a shout and we can also help there.

Tableau connects to SAP BW powered by HANA using MDX query language

This past week, SAP and Tableau announced that you can use Tableau to visualize your SAP BW data.  This is great news and speaks to the openness of SAP BW.  Some people were curious how this works.  It is simple actually.  SAP BW has supported the MDX query language since it was launched in the late 1990's.  There are three ways to send an MDX query to SAP BW:

1. OLE DB for OLAP (ODBO)

2. XML for Analysis (XMLA)

3. OLAP BAPI

Whichever "transport" you use, you will hit the same MDX query processor on BW.  The MDX query language is the same standard used by SAP BW, Microsoft Analysis Services, Teradata OLAP, Oracle Database OLAP Option, Kognitio Pablo, etc.

So, it was easy to connect Tableau to SAP BW because Tableau issues MDX queries and SAP BW supports MDX queries.    Also note that Tableau will work with SAP BW on HANA and SAP BW that runs without HANA.  You can read more and see a demo here: Demo of Tableau running on SAP BW.

Of course, the next question is, Tableau now works on Microsoft Analysis Services and SAP BW.  When will Tableau officially support Teradata OLAP, Oracle Database OLAP Option, Kognitio Pablo, etc?

Is it that easy? "Seven Steps to Accounting Nirvana with HANA"

I was reading a blog post on SDN by Gregory Misiorek entitled "Seven Steps to Accounting Nirvana with HANA".  Gregory show how easy it is to pull ECC data into HANA in order to analyze using an Excel Pivot Table.  If you are considering HANA, this is worth a look.  Gregory's conclusions are:

"Conclusion or the main benefits of doing HANA reporting in Excel Pivot:

1. No need to create custom reports at any intermediate step listed above.
2. Use simple pivot tool which comes with each excel installation "for free".
3. Leverage column storage of HANA with ease of use of Excel to make millions of auditable records available to end user.
4. End users will never ask you to write another report after seeing this but it's up to you if this is a benefit to you and to your customers."

My interest in all of this of course is the underlying technology that makes this possible.  Excel communicates with a dimensional data source using the MDX query language.  If you are using Excel 2007 or Excel 2010, you need a data source that support the MDX 2005 query language.  Products like Essbase or Mondrian only support MDX 1999.  Products like SAP HANA, SAP BW, Microsoft Analysis Services, Teradata OLAP Connector, or Oracle Database OLAP support MDX 2005.  Since HANA supports the MDX 2005 query language as well as OLE DB for OLAP (ODBO), once the data is in HANA, it is just a matter of point and click.  In Gregory's article, steps 1-6 are about getting the data into HANA.  Step 7 is the point and click part of analyzing the data in HANA.

Yes, it is that easy!  I will be presenting a session on how to analyze your HANA data in Excel at the Administration and Infrastructure 2012 Conference which runs Feb 28 to Mar 2, 2012 in Las Vegas.  Come by and let me show you how easy it is to use Excel for your ad hoc data analysis and reporting!

Using Excel on SAP HANA... the inside scoop from SAP's Thomas Zurek

Thomas Zurek, VP for R&D of SAP BW and analytic parts of SAP HANA, just posted a blog about Using Excel on HANA.  This is important information on SAP HANA.  Basically, SAP HANA supports queries using the MDX language.  You can send MDX queries to HANA using the ODBO Provider.  HANA does not yet support XMLA, but it would be natural to expect this sometime soon.  Just like SAP BW has supported the MDX query language from day one, so does HANA.  What is key to note is that in his many presentations, SAP CTO Vishal Sikka has shown various applications connecting to HANA.  In all the hype about new applications on HANA, what has often been overlooked is that Excel can connect directly to HANA without requiring anything else.  What Thomas Zurek points out is that you can use your Excel Pivot Tables to directly analyze your data in HANA.  The power of this solution should not be overlooked when considering how easy it is to do these analytics.  From your Excel desktop, you get the full power of HANA to crunch your data.

OLAP sessions at Teradata Partners conference

I will be at the Teradata Partners User Conference next week in San Diego and wanted to point out a couple of session that are worth attending if you are interested in OLAP analysis on your Teradata data.

The first session is: Seamless Access from Excel PivotTables to Teradata by Sam Tawfik.  The abstract for Sam's session is:

"Teradata OLAP Connector makes it easy for Excel PivotTables to access Teradata. This tool makes it easy for Excel users to navigate the dimensional data stored in Teradata without having to extract subsets of the data.

Extracting data for analysis creates security challenges, inconsistent view of the data, and delay in access to current business data.

This session also includes an Excel to Teradata demo."

The second session is: Introduction to Teradata Business Intelligence Optimizer by Shannon Terry who is Director of Customer Analytics at Nationwide.  The abstract for Shannon's session is:

"This presentation will show the practical application of the Teradata Business Intelligence Optimizer (TBIO) suite of tools in addressing a common problem in organizations: spreadsheet proliferation. Spreadsheets are powerful tools, but they can become dangerous when data is taken out of the data warehouse and improperly handled or manipulated. The TBIO tool suite allows you to embrace the reality of spreadsheet-based BI in your organization while creating a safe and structured environment in which spreadsheet users can leverage value in your warehouse."

Sam's session looks to be a presentation about Teradata OLAP and how you can connect from Excel.  Shannon's presentation is a customer presentation on how they are using Teradata OLAP with Excel.

Also, if you are at Partner, make sure you visit the arcplan booth on the exhibit floor.  The folks from arcplan will be demonstrating how their product allows you to do analysis on your Teradata OLAP data.  Lots to see.

My adventures at SAP TechEd and Sybase TechWave

I was only briefly at SAP TechEd/Sybase TechWave this week.

The biggest thing for me was showing a demo of an MDX Provider for Sybase IQ.  We have worked jointly with Sybase to build this Proof of Concept and we got some good interest from Sybase partners and customers.  If you are interested in getting more information, please follow up with me or Andrew Neugebauer at Sybase.

Of course, the biggest thing at TechEd again was SAP HANA.  Vishal Sikka, SAP's CTO had a keynote where he unveiled two new applications for HANA - SAP Smart Meter Analytics and SAP COPA Accelerator.  You can read more here.  SAP HANA is very interesting because it "delivers single database with native support for row and columnar data stores; a data calculation engine; SQL and MDX interfaces and a unified information modeling design environment."

Starbucks uses Teradata TBIO for Product Affinity Analysis

One of the presentations at the 2011 Teradata PARTNERS User Group Conference & Expo this year is a session by Starbucks explaining how they do Product Affinitity Analysis.  To do this, Starbucks uses a Teradata 2650 Database Appliance, TBIO, Microsoft Excel pivot tables, and Aggregate Designer.  The OLAP cubes are built using the TBIO product with the Aggregate Designer being used to build AJIs to get good database query performance.  Microsoft Excel pivot tables then query the OLAP cubes using the MDX query language for seamless and direct integration.  If you are attending the Teradata Partners user conference, I strongly recommend this session to see what you can do with in-database analytics.  The nice part about this solution is you get OLAP performance on Teradata without having to actually build physical cubes or move any data.  All of the analytics happens inside of Teradata.  You also get the full power of Microsoft Excel without having to learn to use an Excel add-in so the training cost is significantly reduced and you can just focus on the work you need to do.  Details for the session are:

Title:		A Latte with TBIO – Starbucks’s Use of TBIO for Product Affinity Analysis
Length:		1 Hour
Abstract:		This session presents how Starbucks implemented Teradata’s Business Intelligence Optimizer (TBIO) to create a simple market basket analysis tool. Product Affinity & Market Basket analysis techniques are based on the popular reference Data Analysis Using SQL and Excel by Gordon S. Linoff (IBSN978-0-470-09951-3). This presentation illustrates the development of these techniques along with their associated metrics to a large-scale enterprise using a Teradata 2650 Database Appliance, TBIO, Microsoft Excel pivot tables, and Aggregate Designer.
Speaker:		Tim Carter Functional Analyst - Lead Starbucks Coffee Company
Co-presenter:		Paul Sheets Systems Planner/Designer Lead Starbucks Coffee Company

Latest on what Kognitio is doing

Kognitio launched the Pablo product last week and got a nice write up by Doug Henschen at Information week entitled: Kognitio Tries Fast, Faster, Fastest Data Warehouse Strategy.  Doug talked about Pablo and compared it so a similar product from Teradata called Teradata Business Intelligence Optimizer (TBIO).

My comment on Doug's article is that while the comment "Pablo's OLAP-style analysis is also not new. Teradata has offered a virtual OLAP-analysis option and a tie to Microsoft BI tools (including Excel) for several years" is true, Pablo is still a big differentiator with products like EMC GreenPlum, IBM Netezza, HP Vertica, and ParAccel. Teradata TBIO and Kognitio Pablo have what we call in-database OLAP where the OLAP cube meta data is defined and then the actual calculations and processing are done in the database so you get one version of the truth and you leverage the power of the analytics database. This approach well serves the Big Data space for analytics. Other players in this space don't have this approach. They try to bolt cubes on on top of the database and so they don't leverage the performance and processing power of the analytics database. Also, note that this solution integrates with Excel directly. This does not use an Excel add-in like Essbase does. Kognitio Pablo supports the MDX query language and the OLE DB for OLAP (ODBO) interface. What this means is you get the full power of Excel and Excel Pivot Tables directly against your data rather than having to pull your data into Excel and do aggregations and calculations there. While this might seem a subtle difference, it becomes obvious how big an advantage MDX is when you compare performance, scale and functionality. Also, if you every upgrade to a new version of Excel, Pablo will just work. You don't need to wait for the vendor to build an add-in for the new version of Excel. From a user point of view, this is big. So, Pablo is truly a differentiator for Kognitio.

The future of SAP BW - What does HANA mean for BW and BWA?

Simba has been working with SAP for some time on HANA.  We have helped SAP build MDX query language capabilities in HANA similar to what we have helped SAP with on BW for over a decade.  As such, many people ask me what is the future of BW and BWA now that HANA is a shipping product.  The answer is simple: SAP BW is here to stay.  Instead of implementing BW on Oracle or IBM, you can implement BW on HANA with HANA service pack 3.  If you continue to want to use Oracle or IBM for your SAP BW, BWA will continue as your performance improvement option.  If you implement BW on HANA, you don't need BWA because HANA is based on the same performance boosting engine that BWA is based on.  Dan Kearnan from SAP explains very well the scenario of running BW on HANA.

In-database analytics by Kognitio

Kognitio has an interesting session lined up on July 6-7 at Canary Wharf in London that shows how you can do analytics in your data warehouse.  They will be demonstrating their Pablo product which allows you to build virtual cubes and do ad-hoc query and analytics on big data.  If you want more information, click here: OLAP style ad-hoc, exploratory analytics.

The future of Microsoft Analysis Services - for those of us who live in the MDX query language space this is an important read

A recent blog by TK Anand at Microsoft is a very important read for those of us who live in the MDX query language space.  TK is outlining the future of Microsoft Analysis Services, MDX, DAX, and the BISM (BI Semantic Model).  The MDX query language is the de-facto OLAP query language standard used by companies including Microsoft, Oracle, Teradata, SAP, and Kognitio.  Microsoft has been the leader of this standard and it is important to carefully watch the direction they are going in.  I strongly suggest you read this blog post: http://blogs.msdn.com/b/analysisservices/archive/2011/05/16/analysis-services-vision-amp-roadmap-update.aspx.  Of course, nothing happens overnight and there is an entire ecosystem around the MDX query language that will have to understand what Microsoft is doing and determine how they will move based on this.  It will also be very important to see how Excel (the most ubiquitous BI tool) responds to these changes in Analysis Services.

Google Docs now adds Pivot Tables functionality

Very interesting news from Google this week as Google Docs now has pivot table functionality.  While this is a great addition, Google's version of pivot tables seems very basic compared to what Microsoft Excel has.  Excel has had pivot tables for a long time and Excel's pivot tables can work on both relational and multidimensional/OLAP data sources.  Google's pivot tables do not support OLAP data sources.  However, I also heard that Mosha Pasumansky who was one of the inventors of the MDX query language has now moved from Microsoft to Google.  For those who don't know, the MDX query language is the standard query language for OLAP analysis and so this may be a pre-cursor of what is to come at Google.  For more information about pivot tables in Google Docs: http://googledocs.blogspot.com/2011/05/summarize-your-data-with-pivot-tables.html.  For more information on Mosha: http://en.wikipedia.org/wiki/Mosha_Pasumansky.

SAP BusinessObjects Analysis (formerly known as Pioneer)

At the SAP Sapphire conference this week, I spent some time looking at the SAP BusinessObjects Analysis product.  Analysis was previously code-named Pioneer.  This product replaces the BEx and Voyager products.  A very nice product if you want OLAP/dimensional analysis against your data.  There are two versions of Analysis - web and office.  The office version only works with SAP BW and is intended to replace BEx.  The web version works with both SAP BW and Microsoft Analysis Services.

A few points I did note:

1. The Office version seems very similar to Excel Pivot Tables which also works with SAP BW.  I tried to find out what the differences were with Analysis Office and was told that Analysis Office was more SAP'ish than Excel Pivot Tables.  I couldn't really ascertain much difference in functionality though.  Most people have Excel and if it works against SAP BW (at no extra cost), not sure why you would pay to use Analysis Office.

2. The Web version seems very similar to Pivot Tables in Excel Services.  Ok, if you want Excel Services, then you need to also install SharePoint so this could definitely be a reason to go with Analysis Web.  Analysis Web does work with both SAP BW and Microsoft Analysis Services so that is a good thing.  However, it would be great if SAP would extend this to other OLAP/dimensional sources like Oracle OLAP or Teradata Business Intelligence Optimizer.

3. We currently have Voyager (the predecessor product to Analysis Web) working with Oracle OLAP and have had a fair bit of interest for this.  The challenge has been that most customers want SAP to officially support this which they have not yet done.  Note to any SAP people reading this - we have actual SAP customers who have licensed Voyager and really want to have Voyager officially support Oracle OLAP.

Any other comments on SAP Business Objects (SBO) Analysis would be most welcome.

It's nice that OBIEE now supports Oracle database OLAP Option

I was reading on Mark Rittman's blog that the new release of OBIEE now supports Oracle database OLAP Option.  This is great news.  We have been gaining a fair bit of traction with native Excel support for Oracle database OLAP Option using the MDX query language provider and it is great to have OBIEE support as well because this adds another interface to how you can work with your data in your Oracle database.  You can read more here: http://www.obieetalk.com/obiee-11115-and-oracle-olap-support.

Excel BI Survey 2011

How Do Excel and Business Intelligence Integrate in Your Organization?

Simba invites you to participate in a short industry survey on the use of Microsoft Excel in Business Intelligence (BI).  Microsoft Excel is the most-widely deployed and used tool in the BI arena.  This survey is intended to provide deeper insight and understanding for which Excel is used in combination with other applications and as a stand-alone technology for delivering actionable information.  Many companies have told us that their user communities have embraced Excel as the “tool of choice.” We would like to learn how pervasive Excel use truly is within Business Intelligence environments.

The survey will take less than 10 minutes to complete.

Results will be shared with participants shortly after the survey closes on May 18th, 2011.  Results will also be used as the foundation of a future report and white paper.  No individual data will be revealed.

Take the Survey Here 

Thank you for your participation!

Amusing video by Kognitio on how Pablo does not require you to populate an OLAP cube

Kognitio has announced a new product called Pablo which allows you to do in-database OLAP analytics.  Basically, you define your OLAP or cube metadata against the data existing in your WX2 database and the cube is accessible for MDX style queries without having to actually pre-calculate anything.  They have put out a humourous video entitled "Cubeaholics Anonymous" that you can view here: http://www.kognitio.com/pablo-cubeaholics-anonymous.  The concept is really simple, in the past, databases were not fast enough and so you built OLAP cubes and pre-aggregated your data so you could do BI analysis.  Now, databases are extremely fast and MOLAP is not necessary because the performance of a ROLAP solution is very good.  Kognitio's WX2 is a very fast analytics database so ROLAP makes sense.

The benefits of Excel for IT departments

I was reading a blog post from Bill Baker from May last year entitled "I.T. Can Run But I.T.Can’t Hide (from Microsoft Excel)" which had some good points.  Bill talks about how "counter to the conventional wisdom, IT benefits from users serving their own needs with Excel or other tools. In a world of do-more-with less and hyper-competitiveness among companies, IT is pained by being the bottleneck that holds back the creativity and innovation of employees."  I think this is a very important point.  If IT can set users up with the ability to serve themselves using something as simple and pervasive as Excel, IT can become the heroes in the enterprise.  The MDX query language interface to an OLAP cube allows Excel to connect and gives "end-users access to quality data and a tool they enjoy using" for analytics.  At Simba, we have helped companies like Oracle, SAP, and Teradata build this capability into their products.  If you want more information about how to build Excel and MDX query language connectivity for your OLAP cubes, check out: http://www.simba.com/olap-sdk.htm or http://www.simba.com/MDX-Provider-for-Oracle-OLAP.htm.

Inside information about how to connect to SAP BW from Thomas Zurek

Since Simba has been key in the OLE DB for OLAP (ODBO) and MDX query language connectivity to SAP BW and SAP HANA, I get a lot of people coming to me and asking about SAP BW connectivity.  Recently, there was an online thread I was involved in about connectivity to SAP BW.  Thomas Zurek, the VP for R&D of BW, got involved in the thread and I asked him to post his comments on his own blog.  Being the nice guy that he is, Thomas obliged.  Here is a link to what Thomas wrote: http://www.sdn.sap.com/irj/scn/weblogs?blog=/pub/wlg/23784.  If you do anything with SAP BW, I strongly recommend you read what Thomas has written.  After all, he does have the ultimate inside track!

Teradata OLAP Connector - MDX queries and analytics in the database

This month's Teradata magazine has a very interesting article by Matt Zenus explaining how the Teradata OLAP connector works.  Basically, this gives you the ability to do OLAP style analytics right in your Teradata database and access the results using the MDX query language.  You can read Matt's article here: http://www.teradatamagazine.com/v11n01/Tech2Tech/Direct-Access/.

Also, in case you didn't see this, Teradata posted some pretty good numbers for Q4 and the year as a whole: http://www.theregister.co.uk/2011/02/10/teradata_q4_2010_numbers/.

More about Kognitio Pablo

Here is the official press release about Kognitio's Pablo product: http://www.kognitio.com/next-big-thing-in-data-analytics-no-more-physical-cubes.

There is also a good whitepaper by Dr. Mark Whitehorn: http://www.kognitio.com/downloads/pablo_white_paper.pdf. Dr. Whitehorn is the author of "Fast Track to MDX" which was co-authored with Robert Zare and Mosha Pasumansky of Microsoft.  Mosha was one of the originators of the MDX query language.

In the whitepaper, Dr Whitehorn says that "With Pablo, Kognitio has introduced a game-changing environment that enables business users to analyze all of their information from their platform of choice without the need for costly and time-consuming transformations and builds. Fast, simple and available 24/7."  This is quite powerful as Pablo uses the MDX query language to give users direct access from Excel and other BI tools to their data for train of thought type analysis.

 

 

Kognitio Pablo - OLAP without an actual cube - MDX query language access from Excel Pivot Tables

I was at the Gartner BI Summit in London last week and Kognitio had a session on their new Pablo product.  Basically, Pablo allows you to define meta data such that your data in WX2 is presented to Microsoft Excel Pivot Tables as a cube.  So, you really have a ROLAP implementation on WX2.  These ROLAP models are accessed using OLE DB for OLAP and the MDX query language.  There is a session by Robin Bloor of the Bloor Group and John Coppins of Kognitio where they will present this solution and answer questions.  If you are interested in the data warehouse space and how you can build ROLAP models, I strongly suggest you watch this webinar.  You can register here: https://bloorgroup.webex.com/mw0306lc/mywebex/default.do;jsessionid=KGQNNJDNqyPqp0CQxnkybs8NnTQ4ypxf1pHTpZ9v0sg6ns19PDJ3!1821339609?nomenu=true&siteurl=bloorgroup&service=6&main_url=https%3A%2F%2Fbloorgroup.webex.com%2Fec0605lc%2Feventcenter%2Fevent%2FeventAction.do%3FtheAction%3Ddetail%26confViewID%3D279381906%26siteurl%3Dbloorgroup%26%26%26.  The details of the session are:

"The Briefing Room with Robin Bloor and Kognitio

Several new approaches challenge the long-standing process of delivering BI solutions via OLAP on top of Data Warehouses. The most recently unveiled model focuses on delivering 'train-of-thought' analytics to business users in their favorite environment: Microsoft Excel. Under the covers, an in-memory database combines with Massive Parallel Processing (MPP) to achieve a huge reduction in latency, inaccuracy and scalability issues.

Register for this episode of Briefing Room to learn from veteran Analyst Robin Bloor, who will explain how and why the architecture of information management is changing, in part due to the cloud. He'll then offer insights on what you can do to become more agile and responsive. Bloor will be briefed by John Coppins of Kognitio, who will tout his company’s latest offering Pablo, which creates a virtual marshaling area for metadata and super-charged “cubes” which essentially circumvent many of the issues that companies encounter with cube maintenance and proliferation.
Each episode of The Briefing Room includes a 5-min topical intro by the Host, Eric Kavanagh, a 15-min detailed technical presentation by a vendor, a brief response by a well-known analyst, then a live, unscripted analyst briefing. The show finishes with a 15-min Q&A with the audience and anyone who tweets questions with a hash tag of #briefr."

Excel PivotTables with Simba's MDX Provider for Oracle OLAP is a powerful tool -- please use responsibly!

One of the great things about the Simba MDX Provider for Oracle OLAP is that the power of ad hoc query and analysis is now in the hands of the end user.  Gone are the days where you need to submit a request to IT to produce a new report from your corporate BI system, where turnaround is measured in days or weeks.  Now any user can use Microsoft Excel to create their own ad hoc analysis or reports in minutes, with data accessed directly from the Oracle OLAP database, ensuring a single version of the truth.

However, with power comes responsibility. Powerful new tools like Excel PivotTables using the Simba MDX Provider for Oracle OLAP likewise demand the user to act responsibly.  

We recently had a customer that wanted to do some ad hoc multidimensional analysis on an account dimension with 250,000 members and a product dimension with 20,000 members, over time.  In Excel, it seemed perfectly natural to build your PivotTable with these two hierarchies on the same row axis, and then time on the columns, and sales in the measures, and then begin to drill and filter as necessary.  When the performance was not as instantaneous as they have come to expect with the MDX Provider and Oracle OLAP, further investigation was needed.

What is going on here is that Excel is literally asking Oracle OLAP to move heaven and earth to get the data for the report -- this has nothing at all to do with the Provider.   Excel was asking for a crossjoin of two dimensions that would result in 5,000,000,000 rows being returned!

When a DBA is presented with a request like this, Best Practices dictate that they do not do this humongous crossjoin before filtering.   A DBA will first filter on each dimension to narrow the search before doing the crossjoin.  That results in a manageable result set returned in a fraction of the time.

To achieve the same result in Excel, you need to add one dimension first and filter down to just the level you are interested in, then add your next dimension and filter, etc.   That will make the result set from Oracle much more manageable.

Just because Excel and the MDX Provider for Oracle OLAP make something  easy to do, doesn't mean you shouldn’t be careful doing it.  Use Best Practices whenever you are doing analytics between two large dimensions. 

Creating Cubes in Oracle OLAP with Oracle Warehouse Builder (OWB)

Most users of Simba’s MDX Provider for Oracle OLAP are end users, i.e. BI analysts that use Microsoft Excel PivotTables to connect to an Oracle OLAP cube to do ad hoc queries and analysis.  While they care what is in the cube – data needs to be accurate, complete, and up-to-date – they don’t worry about how or where it’s constructed.

It falls into the hands of a cube administrator or a DBA to do the work of creating the cubes.  Usually, this is done with an administrative tool called the Analytic Workspace Manager (AWM), which allows the user to create a multidimensional data model of relational data stored in the OLAP database.  In addition, AWM then allows the administrator to specify the amount of pre-aggregation, compression, and partitioning done on the cube, as well densifying sparse data and administering native Oracle security on the cube data.  The administrator can also create sophisticated scripts to assist with calculated measures and calculated members.

But, AWM is not the only tool for the job.  If you are a DBA or a data warehouse administrator, you may be more familiar with the Oracle Warehouse Builder (OWB) tool.   OWB is more of an ETL (Extract, Transform, and Load) tool that allows the user to integrate various data sources into a traditional data warehouse.  OWB has the capability to do all the dimensional modelling and administrative tasks that AWM can.  OWB is more of a physical layer tool, whereas AWM is more of an business layer tool.  No matter what direction you come from, either tool will get the job done.

That being said, however, there are a few caveats to using OWB for creating cubes that will be accessed using the MDX query language and Excel PivotTables through the Simba MDX Provider for Oracle OLAP.   We have a HowTo document on our website that lists the issues you need to be aware of when using OWB to create OLAP cubes for consumption by Excel users.   While you are there, take a look at the other HowTo documents and videos we have available that give you additional insights on how to get the most of the Simba Provider for Oracle OLAP.

What’s your preferred tool for creating and administering Oracle OLAP cubes?   AWM or OWB?  Why?  Let me know!

Learning to Build Oracle OLAP Cubes for use with Simba's MDX Provider and Excel PivotTables at Oracle University

Last week, two of my Simba colleagues and I had the opportunity to attend an Oracle OLAP workshop for Oracle partners. This workshop was very similar to the OLAP Essentials course offered by Oracle University.   Each of the three of us had a different background, so we all got something different out of the workshop.   

As a Product Manager, I am a geek at heart, and it’s always fun to roll up the sleeves and play with technology.  At Simba, we are MDX query language experts, yet it was still good for me to review and learn about creating OLAP data models, the various views available and their uses, cube security, cube performance and scalability.   Especially useful were the various ways to extract data from an OLAP cube, including DML, SQL, and of course, MDX, as well as the ways where they can be used together.     It is especially powerful to use Oracle DML to assist an MDX calculated measure, to do time based security, and other neat tricks.

During one part of the workshop, various front end clients were demonstrated querying the Oracle OLAP cube.  After the OBIEE demonstration, the class was shown how the Simba MDX Provider for Oracle OLAP enables native Excel PivotTables to connect to the cube and create quick ad hoc reports.  The next demonstration caught me by surprise, however, since I had only heard about it but never seen it live:  we were shown yet another BI analysis tool using the Simba MDX Provider to connecting to the cube.    I can’t name names just yet, but do stay tuned in the near future for an announcement.

I also really enjoyed meeting other Oracle partners and customers.   Many of them were already familiar with our Simba MDX Provider for Oracle OLAP, and several of them had feedback for me, mostly requesting various new features.  We definitely have a full roadmap ahead of us, and we are continuing to add the features that our customers would find add the most value. 

 How about you?  What features would add value for you?  Perhaps you are used to an Excel plugin or extension, and maybe it is no longer up to date or perhaps you would like the functionality to be native rather than through a series of new menus.  Let me know!

‘tis the season for predictions…

On news feeds and podcasts over the last few weeks, there have been lots of predictions of what 2011 has in store for us.  Sprinkled subtly among the hot themes (more mobile, more social, more collaborative), I noticed something interesting in the background—there was a lot of talk about data.  How to handle the ever-increasing growth of data.  How to make data more open and accessible.  How to make sense of increasingly interconnected data.

Whether we’re talking about the latest apps for a smartphone, the latest network that links people together, or the latest technology that helps people work together, at the core there is always the data that is either generated by it or needed by it.  20 years ago, we might have been talking about the latest desktop database technology and how we were going to analyze the data from it and combine that with data from a mainframe system.  It’s still the same problem—we’ve got some large sets of data from different sources and we want to slice & dice that data in a way that makes sense to us.

It’s telling that 20 years ago, the first ODBC driver allowed Excel users to pull in data from diverse sources like dBase and ISAM and produce their own custom reports & charts—and we’re still using the same tools to answer tough business questions today.  The range of data connectivity tools has expanded to include ODBC, JDBC, OLEDB, ADO.NET, OLAP, ODBO, XMLA, MDX and more, but the fundamentals haven’t changed.  My (admittedly rather safe) prediction for 2011 is that the need for connectivity to diverse data sources will continue to grow (and keep growing well into the future).   If there is some unusual or custom data source that you would like to connect your applications to, or pull into your servers from, please drop us a line as it may be simpler than you think.

On news feeds and podcasts over the last few weeks, there have been lots of predictions of what 2011 has in store for us.  Sprinkled subtly among the hot themes (more mobile, more social, more collaborative), I noticed something interesting in the background—there was a lot of talk about data.  How to handle the ever-increasing growth of data.  How to make data more open and accessible.  How to make sense of increasingly interconnected data.

Whether we’re talking about the latest apps for a smartphone, the latest network that links people together, or the latest technology that helps people work together, at the core there is always the data that is either generated by it or needed by it.  20 years ago, we might have been talking about the latest desktop database technology and how we were going to analyze the data from it and combine that with data from a mainframe system.  It’s still the same problem—we’ve got some large sets of data from different sources and we want to slice & dice that data in a way that makes sense to us.

It’s telling that 20 years ago, the first ODBC driver allowed Excel users to pull in data from diverse sources like dBase and ISAM and produce their own custom reports & charts, and we’re still using the same tools to answer tough business questions today.  The range of data connectivity tools has expanded to include ODBC, JDBC, OLEDB, ADO.NET, OLAP, ODBO, XMLA, MDX and more, but the fundamentals haven’t changed.  My (admittedly rather safe) prediction for 2011 is that the need for connectivity to diverse data sources will continue to grow (and keep growing well into the future).   If there is some unusual or custom data source that you would like to connect your applications to, or pull into your servers from, please drop us a line as it may be simpler than you think.