PASS BA Conference Blog

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Category: Advanced Analytics

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.

From the BI/BA Blogosphere: March 22 Update

It's been a busy week! Catch your breath and catch up on what's happening in the business intelligence and analytics world with the community's top bloggers, including a special Big Data focus and a Stephen Few editorial to ponder over the weekend:
 

 

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

Presenting at PASS Business Analytics Conference Chicago, IL, April 10-12

Cross-posted from MarkTab Data Mining
By Mark Tabladillo

I will be presenting a one-day pre-conference and a regular breakout session at the inaugural PASS Business Analytics Conference April 10-12 in Chicago, IL. This large conference requires paid registration. This post has details about the one-day pre-conference on April 10 and the regular conference session. Also, I provide a promotional code for a US$200 registration discount. However, first I will provide a general case for business analytics learning.

Motivation
This term “business analytics” is increasingly being used to emphasize the need for scientific modeling and differentiate with the more common (but still important term) “business intelligence.” I delivered the inaugural session for the PASS Business Analytics Virtual Chapter (online) with a presentation titled “A Case for Business Analytics Learning.” Thoughts I have in that slide deck support reasons why this conference contributes to your own and your organization’s learning about scientific modeling and analytics.

Pre-Conference Session: A Best Practices Cookbook for Data Mining
I am presenting this one-day pre-conference on April 10 with Artus Krohn-Grimberghe, who is a data mining consultant and faculty member living in Germany. Here is the abstract:

Data mining increasingly fascinates business people and information technology professionals alike, with the promise of finding meaningful patterns, relationships, and opportunities in our continuously growing volumes of data. There are tried and tested best practices you can follow to begin and improve your data mining efforts. You’re invited to a full-day data mining seminar with Mark Tabladillo and Artus Krohn-Grimberghe to see these best practices in action. Aimed at the beginning to intermediate data scientist, this pre-conference workshop builds on Mark and Artus’ experience in teaching university students and advising industry clients. Following a cookbook theme for their presentation, they will be explaining and demonstrating their best practices framework by cooking through a data science example from beginning to end, covering these topics:

  • How to avoid mythology while establishing a data science investigation
  • How to apply the best artistry in data cleansing and transformation (shaping)
  • How to apply best practices for machine learning algorithms
  • How to communicate your data mining story within and beyond your organization

The presenters have designed specific breaks during the workshop where you can discuss and interact with them and other attendees. Note that these best practices transcend Microsoft SQL Server Data Mining, applying equally to other software, such as Matlab, Octave, R, SAS, SPSS, and Weka. After this workshop, you and your data science team will have the knowledge and best practices to approach small to large data mining challenges with confidence.

Regular Breakout Session: Data Analysis with R and Julia
R is a free, open-source environment for statistical analysis and graphing. In its almost 20 years of existence, R has remained popular in both academic and business environments. The newer Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. This session outlines functional and performance differences between these two software packages. You’ll see demonstrations of best tips for integrating this software with Windows and walk away with guidelines for working with commercial software.

Promotional Discount
The code BAC698MVP will enable you to receive a US$200 discount from the conference registration fee (attendees who’ve already registered cannot retroactively use the discount code). You can find more information about this conference at http://passbaconference.com/ and register here.

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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