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Big data requires extreme workloads

Read Using Big Data for Smarter Decision Making by Colin White.

Big data involves more than just the ability to handle large volumes of data. It also represents a wide range of new analytical technologies that opens up new business possibilities. But before reaping the rewards of big data analytics, there comes a set of challenges around deploying new technologies into existing data warehouse environments and providing systems that optimize computing performance for different workloads.

As I explored in my recent posts on smart consolidation, the data warehousing and analytics environment is more complex today than even just a few years ago. Many have found that mixing operational analytics and deep or advanced analytics on the same system brings significant challenges to performance and meeting SLAs. With operational analytics, business managers need continuous data ingest and fast access to standard reports with the ability to perform ad hoc queries that drill down into the data and provide new perspectives and insight. When a deep analytical query comes along that requires significant data volumes and extreme computing resources, operational query performance suffers. Big data adds yet another complexity around data sources, data quality, longevity of the data, and whether some of the big data should be integrated into the enterprise data warehouse for longer-term historical analysis.

The best way to handle these different types of workloads is to optimize systems to the workload, and combine these solutions with the enterprise data warehouse to create an “analytical environment”. We see many types of optimized systems in the market today – data warehouse appliances, data marts, noSQL systems, Hadoop-based systems, streaming data analytical systems, cloud-based solutions, etc., that complement (not replace) the enterprise data warehouse. Each system is optimized for a specific workload, and used together they can help streamline and provide fast response to a wide variety of business needs.

A majority of organizations today already understand this – really, optimizing computing resources to various types of data and associated workloads is nothing new. At some point in the data warehouse and analytical environment evolution, organizations reach a tipping point that drives separation of data and workloads. Data growth and new sources of (traditional) data, an increased number of users, increased complexity of queries, and “big data” are all drivers of this tipping point.

Colin White of BI Research wrote a white paper exploring new developments in data warehousing and analytics and the benefits that analyzing big data brings to the business. The paper also reinforces this notion of optimizing systems based on the types of data and workloads. The conclusion – integrating these systems together into a single analytics infrastructure drives smarter and faster business decisions. Read Using Big Data for Smarter Decision Making.

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BIG WOOLLY - BIG DATA!

BIG WOOLLY - BIG DATA!

Wow!  Recent weeks have been full of IBM and third party event travels.  Now that I’m pretty much caught up with day-to-day work, I’d like to talk about a couple of the events I attended and presented at.

TDWI’s Deep Analytics for Big Data Summit was held in San Diego on Oct 3-5.  This was an outstanding event, and I know that attendees walked away with a new found appreciation for the issues of dealing with vast amounts of data and unstructured content.  But more than that, I know they walked away with great appreciation for the advances that IBM is making in this area – clearly leading the field in thought leadership and execution.

We all know that data and information is continuing to explode, and no industry or company is immune from this.  One large (multi-$B) financial services company I spoke to recently more than doubled the size of their data warehouse in the past 3 years, and expects to see it double again in less than 2 years, then double again in about a year.  Imagine, they already have a massive warehouse, and are planning for 4x more in just 3 years (and they may very well race on by that).  Are you prepared for that kind of growth of your data warehouse?

Steve Mills, at IBM’s Information On Demand and Business Analytics Forum in Las Vegas at the end of October, stated this even more firmly.  The world is getting ever more instrumented, interconnected and intelligent.  With data growing in volume, variety and velocity, this poses an enormous challenge on businesses.  But at the same time, it affords an unprecedented opportunity to organize and make sense of it all – to find value and new insight that helps you make better and faster decisions and optimize your performance.  Mills concluded, “We’re at an inflection point where IT is going to change the world in the next decade in ways even greater than that which we witnessed over the last 50 years.”  Hmm, an inflection point, greater than the past 50 years.

Larry lost his hat, and is about to lose his umbrella!

Whoa boy!!  Hold onto your hats and umbrellas!!  The world will NEVER slow down.  We’re only now just beginning to see what can be possible.  The only question is – will you and I be able to keep up?

Let’s peel that onion one more layer:

  • Does your current data warehouse planning accommodate for 2x or 4x data volume growth over the next two years?
  • Have you pulled together “all” your customer data from all of your systems into a ‘single view of customer’?  Single view of product/service?  Single view of…?
  • Can your warehouse and analytics system currently handle structured data, unstructured content, audio, video, XML, etc.?
  • Do you analyze social media to understand market sentiment in real time so that you can immediately leverage positive sentiment or mitigate negative sentiment?

I know that IBM’s BIG Data answer provides different approaches that help you optimize your systems for the different types of workloads.  For instance:

But what I want to focus on here is “Why now?”  Like the Ford auto commercial, “Why Ford?  Why now?”  The question here is, “Why big analytics?  Why big data?  Why real time?  Why now?”

Steve Mills’ talk at IOD certainly hit on this.  But I also like what one audience member at the TDWI Big Analytics Summit said, “Competitive advantage!”  Yes, that’s it!  That’s the answer to “Why now?”  I traveled clear across the country, several times, spoke with dozens of customers, presented customer case studies to numerous audiences, and the big insight I walked away with was…competitive advantage.

If any of you spent time reading or understanding Michael Porter’s great writings on marketing strategy, competitive advantage just seemed so lack-luster to me…at first.  After all, the default marketing message for almost any non-consumer product or service ever created on earth, is that it helps you create a competitive advantage.  Whether they help you create more revenue (taking share away from competitors), reduce costs or improve business processes (be more efficient than competitors), you can tie almost any business benefit to competitive advantage.

So I asked myself if competitive advantage has a different meaning or focus today, than say 5-10 years ago.  I think it does.

Years ago, when the economy was healthy and growing at break neck speed, any dumb company could succeed and make money.  Well, not “any” dumb company, but you know what I mean – you didn’t have to have the best product, nor the best marketing, nor the best sales, but somehow you grew and made money.

In today’s economy, that clearly is not the case.  Good companies with good products, good marketing, good sales, are struggling to survive.  No industry is immune.

Today, you have to be really great at what you do.  You have to understand your customer better than your competitors.  You have to have a product, service or solution that not only meets their needs today, but anticipates and meets their needs tomorrow.  You have to market effectively, and take advantage of all the new ways that your customers want to learn about you and your products.  You have to sell better, working ever more closely with your customer to help them solve their business issues – faster and easier than your competitors.  And, there is far less room today to make mistakes.  One bad decision based on incomplete or incorrect information can make the difference between success and failure.

How do you do all this?  You do it with a trusted, enterprise data warehouse and business intelligence system – consolidating your data and information into a single view of customer, single view of product, single view of ….  You must be deliberate and passionate about your data, deriving ever more insight from it, more quickly than ever before, to make better and faster decisions more confidently.  You need to be creative in what data you look at, how you look at it, and what you do with the new insights you gain.

This notion of competitive advantage is not new.  But what is new is that if you screw up, the consequences are far greater today…and they come faster than ever before.

So back to the topic of BIG DATA & BIG ANALYTICS.  Businesses today are focused on top line revenue growth, reducing costs and improving operational efficiency – optimizing their business across departmental and functional lines.  They have a new found focus here, because the economy won’t let them be lazy.

New business models are forming more rapidly than ever before.  Take the financial services area for instance.  For decades, credit cards, debit cards and a few other services were considered to be leading edge.  Now, peer-to-peer money transfers via smart phones, aircards and a plethora of online and mobile services have emerged.  New services are being invented faster than ever before, and their acceptance in market is happening in hyper speed.  When something takes off, it can really sky rocket quickly!  No wonder the financial services company I mentioned above is growing their data warehouse by 4x, or more, in 3 years.

At the same time, the rapid growth of structured data and unstructured content within the enterprise is being dwarfed by new possibilities for insight from outside information sources and the Internet.  Combine that with huge storage capabilities at low cost, faster processing and better warehousing and analytics software, and the possibilities to integrate and mine new data sources are nothing short of explosive.

Indeed, we are just beginning to see BIG DATA.  Where will we be in 2-3 years?  In 5 years?  Are you ready to exploit new sources of BIG DATA?  My suggestion – you better get ready, fast, ‘cause your competitors are blasting forward.  Your competitors are creating new products and services, optimizing their business operations, listening to their customers and the market via social media conversations, tweaking their marketing messages in near real time, tapping into streaming data to gain insights into data in motion and making decisions in near real time.  Your competitors are learning faster than ever before and gaining new competencies for competitive advantage.  If you fall behind in this business climate, you might not be able to catch up.  Competitive advantage does have a new meaning today.

The question you have to ask yourself.…  Am I moving fast enough?

If you have any hesitancy in answering a resounding “YES I AM”, then you need to check out the IBM solutions mentioned above and reach out to your sales rep asap.

BIG DATA, BIG ANALYTICS, and BIG BLUE … they all go together!

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