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Category: Big Data

Microsoft Keynote Takes Music Tour of PowerPivot, Power View, Data Explorer, and Project “GeoFlow”

In a high-energy Day 1 PASS Business Analytics Conference keynote that had attendees laughing throughout, Microsoft BI’s Kamal Hathi and Amir Netz analyzed the Billboard charts and the effects of American Idol twitter activity using Excel 2013’s PowerPivot, Power View, and Data Explorer - and showed off the new public preview of Project codename GeoFlow on an 80-inch Perceptive Pixel touch-screen display.

Focusing on simplicity, Amir said Microsoft wants to do with BI what "PowerPoint did to the slide projector,” making business intelligence cheaper, faster, and easier. BI needs to be something that everyone can use, he added: BI should stand for "Basic Intelligence.”

The opening keynote also included Dell Software Group’s Matt Wolken talking about the promise of analytics and the opportunity for data pros to use analytics to help drive revenue in their organization. “BI is the fastest growing enterprise application,” he noted, adding that companies implementing BI/BA solutions are 13% more profitable that their competitors.

PASS President Bill Graziano led off with a warm welcome to almost 900 attendees and a call for data professionals to come together to connect, share, and learn beyond the BA Conference. “We are asked on a daily basis to do more with data and within our roles as data professionals,” he said. “There’s a real need for knowledge and support for this growing field of business analytics. As a community of professionals, experts, and partners, we can support and learn from each other as the world of data changes around us.”

Below, check out our Day 1 press release and keynote recaps and articles from press and bloggers (updated as new posts go up) and see how to get the preview of the GeoFlow 3D geographical data visualization add-in for Excel. And tune in to the always entertaining and informative #passbac Twitter stream for the latest news and views.

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

Looking for Big Data Value in All the Wrong Places

Cross-posted from the SQL Server Blog's PASS BAC Preview Series
by Hyoun Park

When Johnny Lee wrote his country classic, Looking for Love (In All The Wrong Places), he wrote with such heart, such pain, and such meaning that you just knew that he was writing about the challenge of creating a business plan for Big Data. For those of you who know the song, you might have missed this detail because you were so caught up in the story. Or perhaps maybe the soothing melody just took you away. But in any case, even a cursory understanding of the lyrics makes it clear that this song was meant to provide guidance to the enterprise analysts and project managers trying to figure out why Big Data is going to help them out.

Just think of the first line, "Well, I spent a lifetime looking for you/Singles bars and good time lovers were never true"

Who hasn't spent a lifetime thinking about how data could help their organization? But the challenges of integrating Big Data into sales, marketing, service, product development, HR, operations, and manufacturing were just too challenging. You could never settle on the correct solution. And when you chose that simple SaaS solution for a one-time need, it never quite worked out the way you expected.

If only there were a roadmap for figuring out how and where to begin in a cost-effective manner. And a way to prioritize how to set a realistic business goal for analytics. And it didn't take a lifetime to find...

"Playin' a fool's game hoping to win/And telling those sweet lies and losing again"

Amen to that. How many promises were analytics supposed to solve? When these analyst firms start throwing around claims like "Analytics pays back $10.66 for every dollar spent," people start to think that kind of return is possible and expected. (OK, I may be guilty for that last statistic.)

But how do you get to that kind of return? How do you play the game of analytics so that this is a realistic business return and not just a sweet lie you tell to your CIO before finding that those returns aren't happening after all?

"I was looking for love in all the wrong places/Looking for love in too many faces/Searching their eyes looking for traces of/What I'm dreaming of"

The vendor landscape for Big Data analytics and data management is enormous. There are a few short lists and short cuts for general analytics deployments, but there are so many specialized tools and new vendors that it is hard to keep up with them. It would be a lot easier if there was a simple way to weed out the contenders from the pretenders without pulling out a full-fledged RfX.

"Hoping to find a friend and a lover/I'll bless the day I discover/another heart ,looking for love."

Somewhere out there is that One True Pairing for your company: Big Data that has the functionality that the IT office wants, the usability that the line-of-business wants, the cost structure that the CFO wants, the support that service and help desk personnel want; and the agility and scalability buzzwords that your executives keep going off about. Should all of these be equally as important? Or are there certain areas where you can skimp on your analytics investment so that you can focus on the areas that truly matter?

"And I was alone then, no love in site/I did everything I could to get me through the night/I don't know where it started or where it might end/I'd turn to a stranger just like a friend."

When you're tasked with building the business case, it sure feels lonely. And you do go out to anyone in Project Management or IT land who has done this before to get some advice. Do I use TCO or ROI and how do I do that without leaving anything out? Am I just looking for some basic business requirements? Will I ever finish this business case or are we just going to end up taking a blind leap into building a data warehouse or implementing a Big Data appliance? Is this going to end up being an all-nighter to figure all this out? Is SQL Server enough or is it time for Hadoop?

"Then you came a-knocking at my heart's door/You're everything I been looking for"

That's the goal, isn't it? Unfortunately, it's probably not going to be as easy as having your analytics solution and all of the value propositions fall in your lap. But there are a number of basic findings that can help you to estimate some of the value propositions you're looking for, such as the keys to maximizing potential ROI, the best way to measure indirect benefits, the four stages of the Analytic Enterprise, the five key components of analytic benefits that Nucleus has identified through over 60 case studies, and attributes that provided Big Data users with an average incremental 241 percent ROI over their existing analytics efforts.

If, like Johnny Lee, you've been trying to build the business case for Big Data in all the wrong ways and in all the wrong places, you should stop by my session at the PASS Business Analytics Conference on April 11th so I can help you find everything you've been looking for in a Big Data business case.

Learn more from Hyoun at his PASS BA Conference session, "Building the Business Case for Big Data."  

 

Business Analytics? There’s a Virtual Chapter for That

As the new PASS Business Analytics Virtual Chapter prepares for its third meeting – a gentle, business-focused introduction to Big Data – you can catch up on February’s presentations and plan to make this free training part of your monthly schedule.

Stacia Misner will take the VC’s webcast stage March 14 for “A Big Data Primer” (noon ET/16:00 GMT) to demystify Big Data, look at its implications for traditional data warehousing and reporting, and explore the technology and skill sets you need to successfully implement a Big Data strategy.

“This is going to be a great real-world session,” notes VC leader Melissa Demsak. “You’ll definitely leave with some inspiration and practical steps for tackling your first Big Data project.”

With a mission to provide quality virtual training to business analysts, BA/BI practitioners and architects, and data scientists, the VC’s focus is on creating a community for shared learning and enabling the creation of world-class business analytics solutions based on the Microsoft platform, Melissa explains.

“Our topics will naturally intersect with those presented by several of our sister VCs – Business Intelligence, Big Data, Data Architecture, and Master Data/Data Quality – but we’ll be covering them from an analytics perspective,” she adds. “We’ll also include non-Microsoft solutions and topics outside the traditional SQL Server and BI community, such as data visualization, analytics, and data science.”

The BA VC meetings, scheduled for the second and/or fourth Thursday of every month, will all be recorded and archived for on-demand viewing. Recordings of the group’s first two meetings – Mark Tabladillo’s “A Case for Business Analytics Learning” and Chris Webb’s “What’s New for BI in Excel 2013” – will be available soon.

You can become a member of the BA VC by simply clicking Join next to Business Analytics in the list of VCs on the PASS Virtual Chapters page. “We'll keep you posted of all upcoming meetings, learning opportunities, and the latest and greatest information from Microsoft,” Melissa says. “We also have a special $200 discount code for the PASS Business Analytics Conference coming up in April – if you haven't signed up yet, just use the code BAC941VC when you register for some nice savings."

Interested in speaking at an upcoming BA VC webinar? Email your ideas to passbavc@sqlpass.org, and make sure you follow the VC on Twitter at @passbavc

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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