I've got to stop mentioning the weather, but it's August in Orlando. Enough said.
IT keeps on moving, and is still exciting. Somehow during the summer (supposedly quiet) season new releases keep coming. Microsoft announced the final tweaks to Windows 7 for its October release – along with the next version of Windows Server. New releases of Citrix's XenServer and open source NetBeans came out in June. Sony's released a Viao Netbook and True Image is now Acronis Backup and Recovery 10 with the July release. And I'm working my way through a whole page of announcements to update TechRef®.
If you're not following me on Twitter, you're missing out on IT news as it happens (at least some of it). Check it out at: susan_semco
Here's the schedule. Summer is a great time for training and to ensure you've got a solid body of knowledge to be ready for the fall uptick.
Here's the schedule or you can view the complete schedule on our Website:
CSTA Web sessions:
August 12, 13
September 16, 17
UITJ (Understanding IT Jobs) Web sessions:
August 13
September 17
TR Web sessions:
September 30
The Cloud Web sessions:
August 26
September 23
Keep in touch - I love hearing from you - and keep up with technology!
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Business Intelligence 2009
BI (Business Intelligence) continues to grow in importance for most companies, and as it grows the technologies and products included under this umbrella heading change. Right now there are several important trends.
The first is the use of open source tools. Both the LAMP stack (Linux, Apache, MySQL and PHP/Perl/Python) and Eclipse are increasingly used in companies implementing BI systems. Many of these tools reflect another trend – the move to incorporating social networking, mashups, and search engines into BI queries. Older tools were batch-mode query tools which depended upon power-users. New tools are intuitive and accessible by business people throughout the organization. Dashboards provided through Business Process Management provide business management with the analytics they need and want.
BI with its dependence on data integration through data warehousing is now moving to incorporating MDM (Master Data Management). MDM recognizes data relationships, and data mining is moving into middleware and application software. MDM is also integrating business models with data models – a necessary step for BI.
Data warehousing is also getting a new look. BI functionality was originally built on top of data warehouses, which were constructed as relational databases or multidimensional databases. New database structures, including column-oriented databases and MapReduce technology are replacing existing systems. Companies have found they had to cancel queries because they simply ran too long. With improved hardware (multi-core servers and parallel processing) new database software allows increased scalability for analytic queries.
Gartner has its Magic Quadrant for BI. For 2009, the Leaders quadrant includes IBM (Cognos), SAP (Business Objects), Oracle, SAS, MicroStrategy and Information Builders. To be included, the vendor must generate $20 million or more in software revenue annually. This eliminates most open source vendors, and Gartner did mention Jaspersoft and Pentaho as viable BI vendors even though they did not meet the revenue requirements.
Finally, BI is moving to the cloud. It's one of the most popular types of SaaS (Software as a Service) applications following CRM (Customer Relationship Management) and is offered by many vendors. So popular that there's even a group on LinkedIn for SaaS BI.
The more companies use BI, the more BI they want. This area will continue to grow in place with other growing technologies. That's one of the things that has always made IT a fascinating industry. A new idea, technique, or product quickly becomes incorporated into existing . . .
You get the picture.
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1. What's a Doorganizer?
2. What's webOS?
3. What technology is used to build large, distributed databases – especially in the cloud?
4. Which of the following does not belong?
Farmer
Hive
Pig
Zookeeper
5. What's Fusion?
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Have you seen the article "25 things You Might Not Know About IBM?" I loved this article. In fact, I blogged about it. And so have many people. I've never really seen this before – one article being picked up by so many to comment on, with everyone encouraging the people they know to read it.
The thing I like best is the picture of IBM and how it keeps up with change. Not just the changes in technology (IBM actually leads there much of the time), but keeps up with social, political, and environmental changes. I'm sure there are a couple of other adjectives that I've missed, but you get the idea. IT does not live in a bubble, it reacts to other changes. This causes innovation in IT which causes changes in the environment, in social structures, etc. It's all a which-came-first game, and IT both leads and follows.
Which takes me to my most common point – keeping up with IT. I've said many times that IT innovation is right now at a high point. The past five years have introduced major changes:
Hardware: multi-core processors, solid state storage;
Networking: wireless improvements and acceptance, same for voice;
Software: columnar/ key-value databases, MDM (Master Data Management);
Combined: Web 2.0, the Cloud . . .
Can you picture the next five years?
Keep up… Keep up….
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Database
Relational design has been dominant in database structure for decades – so much so that other architectures haven't even been discussed. That's changing quickly for two reasons – the cloud and the massive amounts of data companies now store and access.
RDBMS (Relational DataBase Management System) Database structure. Data is stored in two-dimensional tables with rows and columns, and is accessed through SQL (Structured Query Language). Relational databases are the most common database used in IT today.
BigTable Database system used in cloud computing. Distributed storage system for managing structured data that is designed to scale to a very large size: petabytes (quadrillions of bytes) of data across thousands of commodity servers. Built on GFS (Google File System), and used with Google's AppEngine. Development started in 2004, and the database has been in use since 2005. Hbase, part of HaDoop, is an implementation of BigTable.
clustered storage Storage technology. Clustered storage is created by linking multiple storage servers to form a redundant ring of storage devices. Clustered storage systems typically perform multiple read/write requests through parallel access lines to the requesting computer. These systems can scale I/O (Input/Output) for data-intensive applications, they provide simple management as access is through a single system, and users can buy storage as needed and performance and capacity scale as needed. Clustered storage is part of some NAS (Network Attached Storage), SAN (Storage Area Network), and other storage systems and has grown in popularity and passed 50% of the storage market early in 2006. Rackable Systems, Isilon Systems, Exanet, Hitachi Data Systems and Network Appliance are the leading cluster storage vendors.
column-based database Database design. Similar to relational databases, but the structure is based on the columns, not the rows. This means data is retrieved by columns, putting all the like data together. Column-based databases are up to twenty times faster and require up to 90% less table storage space than traditional RDBMSs. Designed for read-intensive workloads such as data warehouses.
Drizzle Simplified relational database system based on MySQL. Functions including views, triggers, prepared statements, stored procedures, query cache, ACL, and a number of data types, have been removed. Designed for Cloud-based applications running on systems that are distributed over 16 or more cores (servers). Runs under Solaris, Linux, Mac OS X, and available from Launchpad.com.
key/value database Database architecture used in cloud databases. The database has domains instead of tables, and domains contain items. Items are defined by keys, which can have a dynamic set of attributes. Each item can have a unique schema and contains all the pertinent information about the item. A domain could contain customer items and order items and data is commonly duplicated between items. Data is accessed through APIs (Application Programming Interfaces) commonly following SOAP (Simple Object Access Protocol) or REST (REpresentational State Transfer) standards. These databases scale easily and dynamically and are good for document-oriented data and distributed scalability.
MapReduce Data management function used to process and generate large data sets. Consists of two functions: Map: a master node takes input, chops it into smaller sub-problems, and distributes those to worker nodes. A worker node may do this again, in turn, leading to a multi-level tree structure; Reduce: The master node then takes the answers to all the sub-problems and combines them in a way to get the output - the answer to the problem it was originally trying to solve. This provides distributed processing and all maps can be performed in parallel, and a large server farm can can use MapReduce to sort a petabyte (quadrillion bytes) of data in only a few hours. Technology was introduced by Google, who uses this technology for their searches. Other MapReduce tools include HaDoop, and Greenplum.
nCluster, nCluster Cloud Edition Relational database. High performance, analytic database used in data warehousing. SQL database that provides "always-on, always-parallel" architecture, and can load 3.6TB (TeraBytes, trillions of bytes) in an hour. Originally released: May, 2008. Version 3.0 released: October, 2008. Cloud Edition works with both AWS (Amazon Web Services) and AppNexus cloud platforms and released: February, 2009.
SimpleDB Database system. Hosted, or SaaS (Software as a Service), system for running queries on structured data in real time. Provides the core functionality of a database, providing the ability to load and query data. Implements only a small fraction relational database functionality. Works with Amazon S3 (Amazon Simple Storage Service) and Amazon EC2 (Elastic Compute Cloud). Opened to public beta: December, 2008.
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1. Doorganizer is a way of remembering your critical stuff when traveling. Hang the Doorganizer on your hotel room (or any) doorknob, stick the stuff (keys, cell phone, notes, money, etc.) you want to remember in its slots, and voila, you're organized. Yes, it's corny. And it comes in red or black. Check it out at Magellans.com.
2. This one is really annoying. It's two different products. webOS is the name of the operating system in Palm's Pre smartphone. And, it's the name of the operating system in Stoneware's webNetwork cloud framework. When will these vendors check to see if the name is already in use!
3. MapReduce. It has two functions: map: a master node takes input, chops it into smaller sub-problems, and distributes those to worker nodes. A worker node may do this again, in turn, leading to a multi-level tree structure; reduce: The master node then takes the answers to all the sub-problems and combines them in a way to get the output - the answer to the problem it was originally trying to solve.
4. a) Farmer does not belong. The rest are all part of Hadoop – a scalable database that uses MapReduce technology. You've got to love the names open source comes up with.
5. Back to reuse of the same name. this one's not as bad as webOS as at least it's just the adjective in both names: Oracle's Fusion is both middleware and application. Google's Fusion is database technology. Moral – always keep reading to get the whole picture.
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