Partner TechTip: How SEQUEL Handles Big Data

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Big data: A big opportunity to improve business.

Big data is one of the biggest buzzwords in IT right now. A lot of companies are clamoring to set up advanced analytics tools and establish business processes that help them make sense of the troves of information now passing through their systems. The goal? To improve decision-making and be in a good position to respond to changing conditions.

 

For IBM i administrators, handling big data naturally creates issues of scale and process efficiency. If you think of big data as having four key dimensions—variety, velocity, veracity, and volume—then it's easy to see that it can and will put considerable strain on traditional storage and database infrastructure, as well as querying methods.

 

In 2012, Walmart collected more than 2.5 petabytes (enough to fill 50 million filing cabinets with text documents) of data per hour from customer transactions. By 2013, it was applying its findings to create predictive shopping lists for Walmart apps and services on mobile endpoints. Perhaps more impressively, it was also using big data to guide customers while they were physically in stores, through QE code scanners and breakdowns of the best-selling products in specific locations.

 

With a technically sound big data setup using SEQUEL, managers can efficiently query multiple partitions of large assets on their IBM i systems, ensuring that they can make highly informed decisions in time.

Managing Big Data on IBM i with Help from SEQUEL


Big data is not without its technical challenges. Legacy business analytics technologies in particular are not well-suited to handling enormous data sets. For example, some organizations may still use legacy Query/400 to scan large files, but tools like this can query only one member of a file at time.

 

Table partitioning, a technique that spreads data across multiple storage objects yet permits it to be accessed as if it were not partitioned, has emerged as a better way to manage large files. Partitions can be grouped by common characteristics such as data or time, letting administrators store massive amounts of data in a single environment that is scalable and easily migrated.

 

SEQUEL allows you to query these multi-partition files and make them an important part of your big data initiatives. It takes advantage of the new SQL Query Engine (SQE) to process many members of a file with a single query; plus it performs its tasks below (rather than above) the machine interface, offering big improvements over Classic Query Engine (CQE).

 

Moreover, SEQUEL offers an IBM i-centric tool for handling big data, capitalizing on the security and scalability of IBM i while also meshing well with other platforms and the unique demands of big data processes. SEQUEL offers, among other features:

  • Information deployment from Power Systems (iSeries, System i, AS/400) on Windows, 5250 terminals, web browsers. and mobile devices (using SEQUEL Web Interface).
  • ViewPoint graphical user interface with intuitive features such as drag-and-drop and scrollable menus for selecting a database, as well as runtime processing to work with specific ranges or sets of data.
  • Comprehensive reporting that can be called from a program, initiated in SEQUEL, or scheduled. Usable formats include PDF, XLS, and CSV, and list-based processes can be used to email or FTP a report to selected recipients.
  • Querying of multi-partition files. Use of table partitioning also enables the creation of databases with virtually unlimited size.
  • Executive dashboards that include business metrics, graphs, and dynamic views of SEQUEL objects such as pivot tables.
  • Remote database support (Oracle, MySQL, SQL Servers, etc.) so that you can access those machines, create consolidated reports, and write ad hoc queries.

 

Through these capabilities, SEQUEL enables superior business intelligence by giving IBM i users quick access to information in large files—even across multiple systems. SEQUEL's combination of flexible data access, intuitive user interfaces, and efficient querying provides just the right mix of tools to get the most out of big data.

 

What's more, you can easily set up SEQUEL objects to get a handle on existing file repositories and legacy query definitions. It's quick and painless to take a Query/400 definition and convert it into a SEQUEL View, preserving all of the programming work you previously put in. Want to learn more about how SEQUEL can make big data work for your company? Contact us for a free demo and trial.

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