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Daily Archives: May 15, 2012
Google uses email to educate on data center and cloud
Cute 'Story of Send' documents an email's journey through the data center
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Google: The Story of Send
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Posted in Cloud computing, data center education, data center security, Energy Efficiency, Engineering, Facilities Management, Global, Google data cener, Google Hamina, google+, Industry News, Internet & Online, Netezza, Networks, North America, Sales & Marketing, Story of Send, USA
Tagged email, Europe, Netezza
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Increasing Profits with the "Best Offer"
My colleague James Kobielus has been talking about “next best” action recently[1][2], and I also talked about this in my post on the importance of agility for analytic applications[3]. I have been talking to a number of customers recently who want to take this beyond next best, to the best offer.
In my blog I talked about a person who had made a number of purchases, and the retailer was trying to influence the customers next purchase by providing them with a coupon for an item that they might be interested in based on their purchasing history. But, how much more could a company make if they could influence their customers’ purchases before they are made, pushing them to more profitable items during the ordering process.
Think of a distributor of auto parts as an example. As the body shops and garages are placing orders, wither online or over the phone, as they enter an item’s description or SKU, what if you could offer a different part, that has the same specifications and same look and feel, but it costs less, and has a higher profit margin for you. Well, that would be a win-win situation, the garage gets a less expensive part that they can sell to the customer for less (like this would really happen, right?) but the distributor also makes a higher profit.
This take more than just a data warehouse / analytic application. And this type of example is where IBM is uniquely positioned to help you out. You cannot build this “system” with just a data warehouse.
You will need an analytics warehouse that can determine the most profitable items. You may need IBM InfoSphere BigInsights to examine your parts catalogs to find which parts have the same specifications and can be substituted for each other. You will probably need a rules storage mechanism that will record the compatible items from BigInsights and also from your internal sales team who have the deep knowledge of the items they sell. Then you need to have both your online ordering system and your internal order entry system must be intelligent enough to pop-up an offer whenever it sees one of the item numbers or SKUs that have been identified as “replaceable”.
While you might be able to call a customer back if you can save them thousands of dollars or more, normally these offers need to be made as the order is being entered/taken, not afterwards.
Bring the power if the IBM Big Data family and our other Information Management and WebSphere solutions to your business, and drive more profit.
SAP lays out cloud strategy post-SuccessFactors deal
SAP announced a broad set of plans to become a player in cloud computing, spanning from a "loosely coupled suite" of business applications to data integration and PaaS (platform as a service) Tuesday during the Sapphire conference in Orlando. Continue reading
New X86 servers from IBM
Flash storage, and blade form factor options added
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IBM’s latest servers include the IBM BladeCenter HS23E for small to mid-sized organizations.
The emphasis i… Continue reading
Posted in Asia Pacific, Enterprise IT, Global, ICT, IT Optimization, Middle East & Africa, Netezza, North America
Tagged Netezza
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Metronode wins NSW consolidation contract
Australian state government data center project will see 130 data center locations whittled away to two
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The NSW Government is consolidating data center activities into two data centers
Posted in Asia Pacific, Australia, Australia data center, Colocation & Hosting, Company News, Construction, Construction News, data center consolidation, Engineering, Facilities Management, Finance & Administration, Global, Government & Public Sector, ICT, Industry News, Metronode, Modular Data Centers, Netezza, New Builds, NSW Government data center, operator, Outsourcing Deals, Project News, Property/Real Estate, Sydney
Tagged Netezza
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HP looks forward to its day in court with Oracle
Welcomes court ruling that trial should proceed and issues strongly worded statement
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HP issued the following statement in response to a court ruling in the ongoing litigat… Continue reading
Big Data: The Data Velocity Discussion
If there’s more and more data arriving and time isn’t expandingi, then data must be arriving at greater and greater velocity.
In my last post I talked about Variety in the Volume, Variety, Velocity triumvirate. There’s more to be said about that… Continue reading
Thoughts on "in memory" data warehousing / analytics
“In Memory” seems to be the latest buzz term in the database and analytics arena. If in memory was able to live up to the hype it would be a great thing, but there is still a lot of hype involved.
In memory database vendors claim that “Reporting requirements have a large impact on I/O time and network resources when dealing with large volumes of data. In order to minimize this, a company needs optimized file and database access methods. In-memory overcomes this process by shifting all the data and workload into memory.” [1]
But this is not the only way to eliminate the I/O bottleneck that can plague traditional databases when they are used for data warehousing and analytics. IBM Netezza solves the I/O bottleneck by pushing the work down to the I/O channel, where it acts on the data as it comes off disk, and only sends the data that matches the query across the server inter-connect.
Because IBM Netezza operates on the data as it streams off of the disks, it is not plagued data not fitting in memory. In an in-memory database, the entire database must fit in memory, and any temporary tables, scratch tables, overflowed sorts, etc. must also fit entirely within the memory the system has been configured to use. As data volume grow, and the “warehouse” becomes more and more visible, there will be more users, and as the number of users increases, the chance that 2, 3, or even 20 or more people will be running queries at the same time, and may be sorting or ordering data using temporary tables. Or, a new user may point and click their way around Business Objects and build a huge query that joins 5 or 10 tables. All of these will cause large temporary tables to be created, all at once, potentially filling up the memory on the system.
So, what happens if an in memory databases uses up all of the system memory (RAM) on a server? Well according to an SAP employee, the system will crash.[2] Does that seem like a good solution to you?
Because of issues like this, most in memory databases are used to run reports and/or analytics on a sample of the data, to restrict the data size to something manageable and affordable. And, as I explained a couple weeks ago, using data sampling for analytics is a bad idea, that will severely limit, if not completely eliminate the value you can derive from your data. Data that you store (some where else, since it cannot fit in memory) and do not analyze is a liability, only when you analyze your data does it become an asset. IBM Netezza ensures that all of your data is a business asset that you can derive the most value from.
There are a number of other points that I want to make on “in memory” databases, but I’ll talk about them in my upcoming posts.
Apple ships first Leopard security update in nearly a year
Apple on Monday issued its first security-related update for OS X 10.5, or Leopard, in nearly a year, to disable long-outdated versions of Adobe’s Flash Player. Continue reading
HK firm ensures toy safety with PLM tool
Toys are fun to play with, but making them is serious business. Hazardous toys from Greater China make great headline-material for US media, so regional toy manufacturers must make extra efforts to ensure that both their materials and finished products… Continue reading
