Big Data Warehousing

IBM's Big Data platform has data warehousing as an integral part of the framework. The IBM datawarehouse capabilities for Big Data include massively parallel processing engine, high performance OLAP and mixed operational and analytic workloads. So IBM's workload optimized systems (comprising of integrated software and hardware/appliances) include both Deep Analytics appliance and configurable Operational Analytics appliances along with data warehousing software.

As part of existing set of solutions available from IBM:

• IBM Netezza appliance is used for high performance analytic queries without DBA tuning or storage administration, where high speed batch ingest and 100s of queries per second is necessary.
• IBM Smart Analytics System is used for both analytic and real-time, transactional workload for the warehouse. Here the workload includes point transactional queries against detailed data, and extreme concurrent query volumes (greater than several 100s of queries per second), and where continuous or trickle feed data ingest is required.

Look out for newer set of solutions to come from IBM's stables in the near future. Also here is an earlier blog post of mine on selecting a Data Warehouse Solution.

Becoming an Analytics-driven Enterprise!

Enterprises can become analytics driven in order to reap the benefits of anticipating demand and immediately matching it, detecting patterns and gaining actionable insights from data flowing in from the different parts of the enterprise, leading to smarter decisions and better outcomes.

Organizations need to have a single, unified view of their data from diverse hybrid operational sources including legacy, real-time, applications and OLAP in order to run "no copy" analytics on this data. IBM Smart Analytics System comprising of integrated Cognos Business Intelligence, integrated InfoSphere Warehouse Enterprise, in-database cubing and mining and deeply integrated and optimized hardware, software and services helps achieve this goal.

InfoSphere Warehouse Enterprise Edition in turn comprises of native hybrid workload capabilities, massively parallel processing, in-database cubing and mining and autonomic tuning and maintenance.

IBM offers the widest and deepest portfolio of data warehouse solutions. IBM Smart Analytics Systems are not just software and hardware "put together" they are engineered to seamlessly and optimally perform for Optimized for Business Intelligence, Analytic & Trans-analytic warehouse workloads. The integrated analytics within the IBM Smart Analytics Systems with capabilities for query and reporting helps you to communicate ERP data quality metrics to the business. 

What is the immediacy for adopting the IBM Smart Analytics System?

It is quite obvious that today's organizations generate large volumes of data from their customers, operations, finance and other departments at a rapid pace. This is in the form of structured and unstructured data that lies un-analyzed. Question is what do you do with these mounds of data? The idea is if this data is analyzed it will provide  these organizations a significant advantage over their competitors as decisions can become data driven rather than based on gut feel (error prone). This data must be put to use immediately and that is what the IBM Smart Analytics System helps organizations do - as these flexible systems can be rapidly deployed and time to value is rapid too. These systems are pre-integrated and optimized with IBM software and hardware based on years of IBM experience. IBM Smart Analytics System provides the warehousing and analytic capabilities which ultimately translate to actionable insights. This also helps improve in areas of productivity and efficiency within operations and enable marketing take more informed decisions. The installation of these systems is a call for action that organizations can ignore only at their own peril, given the fact that such vast amounts of information already exists with them.

Cloud-based Personal Analytics

I joined IBM recently. Newly into an organization as an individual the volume of data and information can start to inundate you. And this is true in most businesses. So what can the individual do? I was thinking why not utilize some tools across the organization.

Cloud-based Personal Analytics:

Use Case:
    * Day to day volume of emails and documents is very high – even for individuals
    * Data insights, analytics or connections between unstructured data may exist
    * Extract/Detect common points
    * Eg: All members of a department person ‘x’ works with, all people involved in a product offering along with their depts

Solution

    * A Text Analytics plugin within the mail client such as Lotus Notes
    * Plugin will connect to an application say Cognos/SPSS run on a cloud
    * Accessible for all major software platforms - Infosphere/Cognos/SPSS so they can be made accessible
    * Used by individuals - results and usage benefits measured inside the workplace