Kognitio launched Data as a Service (DaaS), a new offering to allow organisations with limited financial and staff resources to conduct large-scale data analytics projects on a flexible and cost-effective basis without the need to rely on over-stretched IT departments.
By leveraging Kognitio WX2, an analytical Relational Database Management System (RDBMS), DaaS enables businesses to benefit from true utility analytics as users are only charged for the terabytes/time they use thus eliminating the significant set up, overhead, maintenance and support costs traditionally associated with data warehousing and analytics projects.
Kognitio's DaaS offering is also aimed at departments within larger organisations including marketing, finance and customer service that need to gain fast insight around activities such as campaign effectiveness or customer purchasing patterns without having to be reliant on IT to deliver analysis.
Specifically, DaaS can help with:
* Customer behaviour analysis;
* Customer churn management;
* Basket analysis;
* Weekly and period performance reporting;
* Labour cost management (sales vs. labour);
* Product promotions and pricing analysis;
* Daily performance reporting;
* Business modelling.
Today, organisations regularly gather customer and other sales information in order to ultimately identify additional sources of revenues. However, many often fail to maximise the value inherent in this data because they do not have the capability to analyse this information in depth and in a satisfactory period of time. DaaS is set to change this reality for many businesses as it makes state-of-the-art analytics technology available at a fraction of the cost of installing a bespoke data warehouse appliance.
When compared to in-house data warehousing solutions DaaS offers a number of advantages such as:
* Fast execution - with no software or hardware to buy, install, maintain, or upgrade, on-demand data analytics allows businesses to eliminate the delay associated with the deployment stages. As a result analysis projects can be brought to life quickly and easily;
* Flexibility - the DaaS on-demand model eliminates set up, maintenance and servicing tasks, allowing the IT team to focus on other areas, while simultaneously enabling business users to run even complex data analytics queries directly, quickly and easily;
* Lower costs - DaaS users benefit from being charged for usage only, in granular terabytes/hour increments. In addition, they also benefit from a lower cost of operation because they have access to an optimised IT environment and a dedicated support team on a utility basis. Also, finance directors can amortise their operational expenditure costs across the given contract period; this is much more appealing to them than having to incur large capital expenditure costs for software licenses and hardware that may not get used.
By using DaaS many organisations will be able to gain competitive advantage by exploiting the untapped information asset they already hold. These businesses will have the opportunity to extract, transform, cleanse, model and mine client data to facilitate the provision of the data analytics and business intelligence so critical to today's decision makers.
With regard to data warehousing as a service, Gartner's 'Magic Quadrant for Data Warehouse Database Management Systems, 2007' by Donald Feinberg and Mark A. Beyer, published October 10, 2007, says "We expect the use of this model to increase over the next few years, especially for single business units or a specific data warehouse application. Further, we believe this model will develop into a software as a service (SaaS) model over the next few years for organizations in the small and midsize business category that lack the expertise and funds to support their own data warehouse."
Among the main attractions of DaaS are also the high SLA and security levels it offers: each secure client area is monitored 24/7 to ensure adherence to strict service levels, and physical security, data encryption, user authentication, application security, and other measures ensure that customer data is always protected.