#bigdata (10)

I keep getting asked "Why is Spark so popular?"  My view is it comes down to addressing Four  major requirements :

(1) Easy access to the right data - spark abstracts a lot of complexities when accessing data and handles it in a uniform way using Resilient Distributed Data Sets and DataFrames - more on this in other blogs.  It can access local and remote data - depends on how critical performance is.

(2) Cognitive capabilities - the machine learning capabilities enables Spark to become more intelligent and learn about the data.  Goodbye static algorithms - hello dynamic learning algorithms.

(3) Ubiquity - Spark runs on many platforms and environments so your Spark analytics can run where the data is. It brings the analytics to the data.

(4) Superduper fast - It can all be analyzed in memory,

I'm going to be discussing this in more detail March 1.  But what's your view on why it is so popular?

http://www.worldofdb2.com/events/the-ultimate-platform-for-spark-hadoop-projects

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There is so much focus around big data but the truth be known that the vast majority of data used in big data projects reside in databases such as DB2.  Transactional systems form the back bone of data warehouses from which business analytics solutions analyze information.  But who has the best solutions, what requirements should a customer look for in a solution and vendor?

Watch the highlights from "Transforming big data into insights" : An independent consultant’s perspective" June 24, 2014, 11:00am EDT by clicking here  http://bit.ly/QlXOlG

Guest speaker, analyst and founder of Intelligent Business Strategies -  Mike Ferguson - Writes in his paper :
"The characteristics of Big Data, create a unique set of requirements that need to be met to analyse it. These include:
*Support for the following big data analytical workloads over and above that supported in a traditional data warehouse
*Complex analysis of structured data
*Analysis of data in motion
*Exploratory analysis of un-modeled multi-structured data
*Graph analytics
*Accelerating ETL and analytical processing of un-modeled data
to enrich data in a data warehouse or analytical appliance
*The long term storage and selective re-processing of archived
data (including data warehouse data)"

Join us for this webcast as Mike reveals the requirement to turn big data into real, tangible insight. and receive his full white paper for free.

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Isn’t that the mantra of organizations wanting answers and insights?  IBM DB2 Analytics Accelerator gives you the answers you need 2000 times faster. As part of your analytics infrastructure Accelerator helps transform your computing platform into a uber-efficient hybrid transactional and analytics processing solution. Simply plug it into your infrastructure and without any user intervention or changes to your existing systems, answers to the most complex queries are slashed from hours to just seconds.

Join us for this exciting webcast to learn about the trends and directions of this game changing solution with Dr. Daniel Martin, DB2 Analytics Accelerator for z/OS Architect, IBM.

Register now  for  this new webcast “IBM DB2 Analytics Accelerator : Trends and directions”  Dec 9 2014 11:00am ET. 

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Let me put this the number of 2000 in perspective. Imagine arriving at your destination 2000 times faster.  Think how that might revolutionize your daily life

Business agility has never been so crucial to winning in the market place. Organizations are on a quest for more insight fast than ever before - to help detect and prevent fraud in near real time – to identify and make an offer to a customer while they’re in a store based on previous browsing history and geographic location.

IBM DB2 Analytics Accelerator for z/OS gives you that capability today. As part of your analytics infrastructure Accelerator helps transform your mainframe into a uber-efficient hybrid transactional and analytics processing solution. Simply plug it into your infrastructure and without any user intervention or changes to your existing systems, answers to the most complex queries are slashed from hours to just seconds.

Join us for this exciting webcast to learn about the trends and directions of this game changing solution with Dr. Daniel Martin, DB2 Analytics Accelerator for z/OS Architect,

Register here bit.ly/IBMAccelerator-LI for IBM DB2 Analytics Accelerator for z/OS – trends and directions webcasts. Dec 9 2014 11:00am ET.

#Analytics #bigdata #System z #DB2forZOs #CICS # Accelerator # IMS

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There they sit - in the restaurant a family together - but apart. Heads down in their virtual and social worlds engrossed on their mobile devices.  Food arrives and they're back to the physical world.  And all the time - organizations are watching, collecting data on them.

Why is mobile such a phenomenon?  These devices are always on. We visit 120 screens a day on our mobile devices - checking things, socializing, purchasing on line.  To businesses - mobile adds 2 new important dimensions to analytcis - time and place - in addition to all the rich information we generate. Organizations and retailers can offer geographical, time critical and content-specific offers to encourage customers to make that purchase decision in the “mobile moment".

Executives need to stay in touch with what is happening in their businesses 24x7 - in the office, at home, in a cab. on an airplane. Is now the right time to make that decision? Should we invest / divest ? These always-on, smart connected devices have become the mobile office, enabling users to make smarter decisions at the right time. So mobile devices are driving real-time and personalized business analytics. It's unacceptable to wait for a response on a mobile device. Mobile users seem to be calling the shots. In the UK the #1 reason why the "Millenials" (20-30 age group) switch banks is they don't like the mobile app.

So what does this mean for organizations with DB2?  Well if you have DB2 for z/OS - or IMS - you in good hands.  System z just scales and DB2 for z/OS is enabled for mobile device development with full support for MongoDB.  It delivers immediate access to the very latest transactional data - not a cached out of date copy. Add DB2 Analytics Accelerator and complex queries are slashed from days to seconds which means complex predictive and anti-fraud models can be refreshed hourly instead of weekly to help reduce the ever increasing business risks.

If you want to learn more join me and my co-speaker Adrian Lurie for "Mobilizing the enterprise: Business anytime, anywhere" on Nov 11 2014 at 11:00am EST.
Register here http://bit.ly/MobileAdvantage and receive a free thought leadership paper "When 'pull' turns to 'push': Mobile computing is now mission critical"

Mark Simmonds @zbigdata

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Any body watch the the launch of the IBM z13?  Wow - what and incredible piece of technology.  I blogged earlier back in December on mobile and analytics colliding.  It really has created a new tipping point in the industry.  Mobile iss driving business analytics to real time and analytics are gaining more insight from the tidal wave of mobile data and transactions that are being generated.  Think about it.  How many time do you access you cell phone in a day, in a week in a month, in a year !  All that lovely data.  There is only one database that can managed this workload. And now the z13 does it faster, smarter and more integrated than ever.  To find out more join me and Rebecca for a new webcast on Jan 27 11:00 ET on "When Mobile and Analytics Collide : Are you prepared?"  Hey - you get a free white paper !

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Just register for the Jun 24 2014 webcast "Turning big data into trusted insightshttp://bit.ly/QlXOlG
#bigdata #analytics #insight #intelligence #DB2 #DB2zOS #hadoop #CICS

Join us for a complimentary webcast led by guest speaker Mike Ferguson, an independent consultant, analyst and founder of Intelligent Business Strategies. Wondering what to look for in a vendor when it comes to implementing big data and business analytics solutions? Mike reviews the business and technical requirements for clients embarking on these initiatives as well as some of the key IBM solutions for System z and their potential to help clients meet those requirements.

Register and receive Mike's new white paper on this topic

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A couple on months ago I decided it was time to update my router so I started searching on the web.  I saw the latest wireless specs were 802.11 ac. So I found a few routers started comparing their capabilities against my list of needs (coverage and range, reliability, management, speed, cloud enabled, media server enabled, auto failover to second ISP... and so on.  After I narrowed it down to 5 or 6 models, I started looking at reviews on Amazon, CNET, Trustedreviews, etc and weeded out the weaker ones.   I contacted friends on social media sites who were tech-geeks like me to hear their experiences, physically looked at one in a store  - yes... I actually stepped outside the somewhat safe virtual world for a while!. Once I had decided the "chosen one" met all my requirements / needs and was satisfied with the reviews I started looking for the best price on-line and fastest delivery. By now you're asking "Where is he going with all this?"

It occurred to me that I was using many sources of information :
structured information comparing specs in tabular form
free form text reviews containing emotion and sentiment
1-on-1 conversations with friends
cheapest prices, fastest deliveries....

Bingo ... big data - and analytcis !

So do big data and analytics processes mimic how our brains work ?  We take multiple different threads, many perspectives, analyze all these thought processes (somewhat in parallel).  You can see where I am going with this....  We start with a set of objectives, gather a few data points with some uncertainty about the best outcome at this early stage and then add more perspectives and data points, join the dots, keep adding more data points, connect more dots until we feel we are as close to making the best decision that meets our needs.

So to me - we have always been doing big data and analytics mentally. But now we're trying to emulate it in computer models.

Deep.... very deep.

So when you are trying to decide what is the best big data and business analytics and solution and trying to identify the best vendor,  here's a link that might be helpful. http://bit.ly/QlXOlG
Register here "Transforming big data into insights" : An independent consultant’s perspective" June 24, 2014, 11:00am EDT

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When Mobile and Analytics Collide

How many dimensions are there to analyzing data?  Strange question?  Sit tight.....

When we analyze data we look for insights - meanings, patterns, correlation of events that might help us identify and lower risks - similarly with costs - or we might look for opportunities to increase market share, revenue and profit. We might want to understand what happened in the past and why; run what-if scenarios or try to predict what might happen next with degrees of confidence.  We may want to just investigate in an ad-hoc fashion to see what emerges (opportunistically).  All this to strive for better business outcomes.

With me so far ?  Good....

Then along comes that army of smartphone users - yeah, you and me included, browsing, searching, communicating and making purchasing decisions. We want to know NOW.  We want to buy NOW. We want to make that decision NOW. The NOW is governed by our impatience and the need for instant gratification but sometimes it is driven where we physically are - at home, in a store, at a concert, in an emergency situation, in a grief stricken moment.  So this disruptive device has added time sensitivity and geo-location dimensions to the mix - driving analytics to real-time and therefore business critical analytics.

Thirsty for more ? Register for this webcast ---- Hey.... You get a complimentary white paper  :)

Merry Christmas and a Happy New Year..... Really?? You asked for new smartphone???  Peace out!

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