It’s a now a little over a year since SAP launched its High-Performance Analytic Application (HANA) at its 2011 SAPphireNOW event. And, it seems that many organizations dealing with Big Data – particularly those looking to leverage data at real-time or near real-time pace – are turning to HANA. At the recently held 2012 SAPphireNOW user conference, SAP boasted almost 57,000 HANA end-users and seven different hardware partners.
The buzz around HANA – particularly in the SAP world – is gaining momentum. SAP plans to roll out support for the enterprise resource planning (ERP) module, within its flagship Business Suite product family, on the HANA in-memory database platform. This development is penciled in for the fourth quarter of 2012, with other Business Suite modules to follow.
But what’s the big deal about SAP HANA – what makes it different from a crowd of emergent databases aimed at addressing the proliferation of enterprise data, and which types of organizations stand to benefit from its unique capabilities?
What’s the big deal about SAP HANA?
Well, HANA – a data warehouse (DW) appliance designed for processing high volumes of transactional and operational data in real-time – is able to copy and synchronize data from a DW or other application (ERP for example) in real-time.
Therefore, by running in parallel to a source application, HANA enables end-users to query expansive data sets in real-time – users don’t have to wait for scheduled reports to run before they begin data exploration.
According to SAP, HANA can scan 500 billion Point of Sale (POS) records in just seconds.
Additional database support in Yellowfin 6.1 targets Big Data
So impressed with HANA’s ability to query multiple types of data sources, in real-time and at unprecedented volumes, global Business Intelligence (BI) vendor Yellowfin announced that it had added support for HANA, and a range of databases, in the latest release of its BI software (Yellowfin 6.1).
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Why are solutions like HANA going to become increasingly important?
So why has SAP HANA found such a receptive audience? The reasons are three-fold and part of an overarching trend towards data saturation:
- The cost of technology and techniques for collecting and analyzing enterprise data to produce meaningful and actionable information is dropping significantly. That is, organizations are now collecting more information simply because it’s viable to do so.
- The rapid expansion of existing data sources.
- The emergence of new data sources and types – think social media.
In fact, market research firm International Data Corporation (IDC) predicts that the volume of data generated per year will reach a staggering 35 zettabytes – that’s equivalent to 35 million petabytes – by 2020.
Research and advisory giant, Gartner, predicted in its recent report – Pattern-Based Strategy: Getting value from Big Data – that worldwide data volumes are growing at a minimum rate of 59 percent per year.
What’s particularly noteworthy, is that organizations that collect larger amounts of data are also expected to generate meaningful reports based on that data in shorter timeframes.
Aberdeen Group’s report Big Data, Big Moves found that 78% of organizations reporting off Big Data sets (those organizations reporting off data sets from 6 terabytes to more than 1,000 terabytes) had to deliver reports within a day of a request being lodged, with 27% requiring data delivery at near real-time speeds.
In stark contrast, only 50% of organizations dealing with ‘small data’ (organizations reporting off data sets of less than 6 terabytes) had to deliver reports within a day of a request being lodged, with just 10% requiring data delivery at near real-time speeds.
This marriage, of proliferating volume and demand for speed, represents a significant challenge for many organizations as they attempt to leverage their data assets for competitive advantage, and a vast opportunity for products like SAP HANA.
Where to next?
Tune back in for part two of this two-part series to discover how together SAP HANA and Yellowfin can deliver real-time business value to business users, find out why the need for BI IT-business collaboration is intensified when implementing Big Data analytics, and learn The Data Warehousing Institute’s (TDWI) top five strategic tips for achieving an effective Big Data analytics program.