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Category: Strategy and Architecture

Exciting Times for Business Analytics

Cross-posted from the SQL Server Blog's PASS BAC Preview Series
By Marco Russo

We live in exciting times from the point of view of data analysis. Nowadays, the problem is no longer how to find the raw data, but how to handle the pressure of data coming in from so many places. At the end of the day, the goal is always the same, extracting useful knowledge from data. This has been the goal of Business Intelligence (BI) since 1958, when Hans Peter Luhn used this term for the first time. In more than 50 years, the technology evolved, increasing the manageable amount of data and lowering the related costs. However, it always required professionals who were able to create and refresh the data model, empowering end users with canned reports and data navigation tools. A common issue in this process was the gap between people who knew the business and BI developers. In the best case, this gap produced long development times. In the worst case, it led to project failure.

Today, this gap can be drastically reduced. Thanks to Self-Service BI products, if you know your business, you can create a data model without having to ask for a BI professional consultancy. However, a common mistake is thinking that these new technologies are meant to kill the traditional data warehouse approach, i.e. the Corporate BI. In reality, self-service BI is an opportunity to improve the ROI of a properly built data warehouse, even if an optimal architecture might require some adaptation to the data warehouse schema, in order to simplify and optimize the extraction of data for self-service BI purposes.

When we use the term Business Analytics we refer to the exploration and investigation of data. This requires the usage of statistical methods and data visualization, and oftentimes needs adapting the data model. The PASS Business Analytics Conference (PASS BAC) in Chicago this April is the right place to go to learn more about tools, methodology and best practices in the Business Analytics area.

I will speak at the PASS BAC in two sessions about the state of the art in self-service BI:

  • In the session Self-Service Data Modeling, I discuss the challenges of creating a proper data model by using Excel 2013 and PowerPivot. Thanks to the DAX language, it is possible to apply few transformations to the raw data. However, preliminary data preparation might be necessary and users that do not have a knowledge of ETL and SQL need other tools and techniques to adapt their raw data to the required model. I will show how to solve these issues in common scenarios, using tools designed for end users and not for BI developers.
  • The second session, Modern Data Warehousing Strategy, is about changes in the Data Warehouse architecture and modeling required to face the challenges of the self-service approach and the new demand caused by Big Data technologies such as Hadoop (HDInsight). A good data warehouse is still the optimal starting point for any analysis, but we need to update our strategy for data warehouse implementation to fit the requirements of this new era. What kind of data modeling should we use for the data warehouse? What is the role of data marts? Do technologies such as PowerPivot or Analysis Services Tabular affect the way we should model our data? Do columnstore indexes remove the need for an analytical server like Analysis Services? We will discuss these and other questions, offering an updated approach to the data warehouse modeling methodology.

Look at the many other sessions available in the program and join us in Chicago at the PASS Business Analytics Conference!

From the BI/BA Blogosphere: March 29 Update

It's a Good Friday to catch up on your business intelligence and analytics reading with the community's top bloggers:

Why I Am Attending PASS Business Analytics Conference in Chicago

Cross-posted from BI with an accent...
By Rafael Salas

The PASS BA Conference is less than 3 weeks away, and if you are still pondering whether to attend, let me share with you a few good reasons – my reasons, of course – to attend.

  1. Catching Up. The last couple of years, the analytics and BI landscape has experienced dramatic changes as new technologies make their way in, and the heavy buzzword marketing machinery from vendors makes it harder to separate the wheat from the shaft. You can use this conference to see if Big Data is really for you, or to get your head around advanced data analytics, and perhaps to find out if data science is real or just marketing fiction.
  2. Agenda & Speakers. The lineup of speakers is great, and the topics are well balanced across 5 different tracks that promise to deliver first-hand, real-world experiences: Big Data, Advanced Analytics, Data Visualization, Information Delivery and Collaboration, and Strategy and Architecture.
  3. Networking. Yes, the usual but important part we tend to miss when we go to conferences. Being around 1000s of professionals with similar challenges and interests is a unique opportunity to get connected and learn how others are doing it.

I will be one of the PASS networking ambassadors for Thursday's evening event and will be hanging out at either the Experience Lounge or the Microsoft Kiosk, so if you decide to attend,  please make sure to stop by and say "Hi."

This is a 2-day conference plus a pre-conference day. Registrations are still open, and you can get $200 off the registration fee by using  code BAC945MVP.

McDowell Interview: PASS Business Analytics Conference, Microsoft Data Mining

Excerpt cross-posted from KDnuggets
By Gregory Piatetsky

I interviewed Douglas McDowell about the PASS Business Analytics Conference, SQL Server, Microsoft Data Mining, less known but useful features of SQL, NodeXL, Big Data and more.

Douglas McDowell is the CEO of North America for SolidQ (www.solidq.com). He is a Microsoft Most Valuable Professional (MVP) for SQL Server and serves on the Board of Directors for the Professional Association for SQL Server (PASS). He is an author and contributing editor for SQL Server Magazine.

I spoke to Douglas ahead of the PASS Business Analytics Conference in Chicago April 10-12. (Note: KDnuggets readers can save $150 when you register for the PASS BA Conference by using the BAC13KDN discount code.)

GP: What is the  PASS Business Analytics Conference?
McD: It's a very exciting time for data professionals as more and more organizations turn to data-driven insights to stay ahead in today's competitive marketplace. Staying up to speed in this constantly changing world of data can be a challenge - that's where the PASS Business Analytics Conference fits in.

The conference was established to meet the needs of a growing Business Analytics community affiliated with Microsoft technologies such as Excel, SharePoint, SQL Server, Parallel Data Warehouse, Azure, Hadoop and more. The event is geared towards data and business analysts, data scientists, architects, and business analytics/business intelligence professionals and covers a wide range of information from data exploration and visualization, predictive analytics, content management and architecture, information strategies, and much more.

GP: What is the role of SQL Server in the Microsoft eco-system?
McD:
As a partner and insider I have listened to Microsoft's vernacular shift from "SQL Server" to "Data Platform" and other similar terms. Some might think it a de-prioritization of SQL Server, but that would be a mistake. Microsoft is focused on the exploding business analytics (BA) needs of clients and understands it requires a complete toolbox of complementing technologies to deliver it all. As far as I can see, SQL Server is and will be a core component to BA for Microsoft going forward. Whether it be in the cloud or on-premise, SQL Server will hold critical features and therefore the Microsoft licensing model for core BA functionality. I see SQL Server getting more robust and more integrated with the rest of the Microsoft BA platform (since SQL Server will not and should not contain everything). ...

Read the full interview

Business Analytics and PASS: Yes, Please!

Excerpt cross-posted from Mark V SQL
By Mark Vaillancourt

Over the past few years, I have been truly amazed at the power of business analytics. I know that part of that is due to my increased exposure to it through client projects. But it seems clear to me that the understanding of what analytics brings to the table has grown as well. One example of the rising prominence of analytics is the fact that IBM is paying out marketing dollars on prime-time commercials about it. From my perspective, that is neither insignificant nor a coincidence.

More and more companies are realizing their data isn’t some static asset that they should just stick onto disks like people used to hide money under their mattresses. It has value far beyond just keeping accounts up-to-date or being able to show many customers bought Jiffy Pop last week. That is information. And that is certainly important. But analytics takes us to another level entirely.

A client recently told me that his company has gotten really good at measuring operational metrics. Data can help you do that. But analytics can help you determine if you are measuring the rights ones in the first place. Suppose your company can tell the efficiency of Process XYZ with amazing precision, and managers all over the company spend a lot of time, both in and out of the office, worrying about how it will fluctuate. Quality business analytics could help you show them how much of an impact Process XYZ actually has on company success. You may end up lowering the company’s overall healthcare costs by preventing a few ulcers.

I am actually just finishing an SSAS 2012 Tabular Model for the client above in the next couple weeks. It is the first business analytics project in his company. It is just a Proof of Concept, and it is not yet complete, but he keeps telling me how valuable it has already been. It is allowing him to correlate data points he never could before. While it is a short project, and the team is just me and a part time PM, I am trying to keep it in the Agile vein and releasing new versions to him every few days or so with new fields, new measures, etc. Within about 5 minutes after I made the very first release, he told me that he had been able to prove a theory about what was causing a particular business pain, a pain that went up to the highest levels of his company. My point with this is that analytics can often help us see things from different angles or perspectives that are otherwise impossible.

I just can’t wait to get this into the hands of more people in the company. Then we will really see what, I think, is the greatest benefit that business analytics provides: Questions. You read that right. Not answers. Questions. Answers are great, and analytics can provide those. But questions are the gems. Truly successful business analytics will lead you to the questions you didn’t know to ask.

If you work in a company that has data, then you work in a company that is likely to benefit from business analytics. We, as a global community, are producing and consuming ever increasing volumes of data and at increasing speeds. Analytics is no flash in the pan; it is here to stay, and the appetite for it will only get larger. The sooner you start learning about it, the better. The PASS Business Analytics Conference is an excellent place to start. You can register here. Your career is worth the investment. Who knows? Maybe you could end up leading your company (and yourself) into an era of better insight and success than ever before.

Note: Join Mark and co-presenter Doug Lane at the PASS BA Conference for Hailing Frequencies: Analysis Services Terms and Concepts – a Star Trek-themed introduction to the terminology and ideas important for business analytics projects using SQL Server Analysis Services.

Musings on a BI Career: Past and Future

Excerpt cross-posted from DataInspirations.com
by Stacia Misner

I wasn’t going to do it. The whole recap of the year just retired. The goal-setting of the year just arrived. But I did find myself having to plan a few things – plan for customer visits and activities, plan travel for upcoming events, plan time to prepare content for those events, and so on. And as I thought about those plans, I couldn’t help but ponder where I’ve been and where I’m going, and thus this post was born. …

Accidental Business Intelligence? Not Really
I always think of my career in BI as accidental, although taking a longer view I realize that it really wasn’t. In February 2011, I told my story to Andy Leonard (blog | twitter) as part of his SQLPeople series of interviews. There are some karmic aspects to that story that I would never put in print, but I’d be happy to tell you in person someday if you ask nicely.

In that story, I mention working with Lotus Notes. In the late 1990s, I had this feeling that using technology as a knowledge management tool was an attainable goal and put a lot of energy into learning how that should happen. But then I got deflected into business intelligence, which turned into a fascinating and rewarding career. But all along, I had this nagging feeling that BI was just part of the story. I wasn’t satisfied with just delivering on reporting and analysis. As important as that is, I believed additional transformation in the way we work with data and with each other was necessary in order for BI to fulfill its promise.

Collaborative BI
I’ll admit that in the beginning, I wasn’t very impressed with SharePoint – I believe it was SharePoint 2003 when I was first introduced to it. I had been working with Lotus Notes long before that time and felt that it could run circles around that release of SharePoint. Full disclosure – I haven’t looked back at Lotus Notes since I left it, so I have no idea of its capabilities today. But starting with SharePoint 2007, I started thinking beyond the traditional dashboard compilation of scorecards and reports. I was thinking about unstructured data to support the structured and would mention it in my presentations and classes. Then with SharePoint 2010, I started thinking about the collaborative and social aspects and started putting these pieces together with ideas that I had been nurturing since the late 1990s. And so, a presentation was born for a webinar, a few SQLSaturdays, and continues to evolve as I gear up for the PASS Business Analytics Conference in April 2013. Because an hour presentation only sets the stage for some of my ideas, I have set up a Collaborative BI resource page that will grow as I commit these ideas to writing.

Big Data
Meanwhile, the buzz around Big Data became louder in 2012. Now I’ve been around a few years, and I’ve seen buzz come and go. I had plenty to keep myself busy meanwhile during 2012 and just watched and waited to see what would happen. And then things started to get interesting. So much so that it’s time to start talking about it. Consequently, I am working on presentations on this topic throughout the year (keep an eye on Upcoming Events for online and in-person events), including a session at the PASS Business Analytics Conference on Power View and Hadoop in collaboration with Joey D’Antoni (blog | twitter). And that’s just the beginning. I plan to add another resource page for my thoughts on BI and Big Data. Watch for more blog posts and presentations.

When I think back to my “accidental” discovery of BI and the ideas we were throwing around at the time, I realize we were a bit ahead of our time. What we needed at that company to achieve those big ideas was Big Data – we just didn’t call it that then. We started on a much smaller scale and focused on data warehousing and reporting and analysis tools, and we were barely ready for that then. I work with customers today who are still barely ready for that.

Data Science
But now in the era of Big Data and data science, I start thinking about those big ideas again and how much more attainable they are today, 14 years after I started down this path. The BI world is poised for the biggest change I’ve seen in my career. While I cannot share the specifics of what we were thinking about in my R&D days, I can try to explain how I see the difference between BI as we traditionally think of it and where data science can take us.

BI helps us understand what happened or what is happening now, using established processes and tools. Although BI can scale quite dramatically, scale introduces some complexities that in some ways limits the types of reporting and analysis that we can do. Data mining is often included in a discussion of BI technologies, but its use has not been very prevalent in my client base. Data mining can not only be used to explore data to help us understand what happened, but can also be used to predict what might happen. And this is where we see data science come into play now. Data science can help us look forward and to predict an outcome or a correlation. It incorporates many techniques that are common to data mining, but it can go beyond those techniques as well. We can work with larger data sets than ever before because we can store data more cheaply than ever before and we have better tools for dealing with these larger data sets using commodity hardware.

Is the Data Warehouse Dead?
No, I don’t think so. At least not completely. There’s still a place for operational and mission-critical information that’s been consolidated, cleansed, and corporately-sanctioned as truth. I don’t really care what we call that information source – a data warehouse, a data mart, whatever. We need access to that type of information because that’s how we decide what to do today to achieve our goals, respond to specific problems, or show the board (or the world) how we’re doing as a business. The new potential with Big Data and data science is the opportunity to explore data in ways never before possible. We don’t know what the opportunity or business value in that data might be until we examine it in new ways or combine it with other types of data – data that was captured by others and shared publicly is just one example. Creativity is key. But like traditional BI, in my mind, it’s all useless unless we can DO something with that information. And of course, we need to share and collaborate!

What do you think? Is BI as we know it going to die or thrive in this brave new world of big data? I look forward to delving more into these topics more in future posts. I hope you do, too!
 

  
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