The next big IT infrastructure trend is here: Analytics-as-a-Service (AaaS).
We’ve seen how data can deliver insights in the hands of people like Hans Rosling, who has been listed amongst the 100 most influential people in the world by Time magazine. Rosling has shown the history of 200 countries over 200 years using 120,000 data points. He presents data with the urgency of a sportscaster and brings in the visual panache of movie directors like James Cameron (Avatar).
You can’t help but be romanced by what data can do. And you can’t help thinking about why Rosling is a rock star today: because businesses worldwide are starting to see data as the super food of analytics. David McCandless, the author of Information is Beautiful, calls data “the new soil” because it can give rise to new ideas, insights and wealth.
The McKinsey Global Institute points out that the potential of that data, as an example, is €250 billion to Europe’s public sector administration (more than the GDP of Greece). In more recognizable terms, it has the potential to bring about a 60% increase in operating margins for retailers. Naturally, the demand for what can be called Sensemaking IT Infrastructure to predict the future is on the rise.
- This has an inevitable implication: Analytics-as-a-Service will be what businesses shop for. Infrastructure for data aggregation using Cloud models will be on the rise, self-service models for tools in Cloud will become critical, and a whole new range of data and analytics appliances will become part of the IT infrastructure provider’s arsenal.
- Storage and Data warehousing: Data is growing in complexity. Datamarts and warehouses must keep pace with the volume and velocity of data as well as the variety that includes structured and unstructured data in different formats like text, voice and video. In an effort to be agile, businesses will avoid investments in storage solutions that lock down their ability to keep pace with changing storage needs and opt for elastic and scalable outsourced pay-as-you-go Cloud solutions. In addition, because of the huge amount of data, businesses will demand intelligent storage solutions that bring down costs through compression, can separate and store process data from regulatory data, are capable of data tiering and can provide advanced capability through rapid content access and remixing.
- Tools: There will be an increasing demand for highly scalable tools such as Map Reduce and Hadoop that enable distributed computing for large data sets across commodity servers. Tools that manage traditional and non-traditional data sources, millions of events every second, can reduce latency to microseconds and run on a variety of hardware platforms will be the most visible trend before customization takes over. Concurrently, industry specific sensemaking algorithms (and visualization tools) that can dig into the data to improve a business’s ability to make quick and accurate decisions are witnessing increasing demand.
- Appliances: The role of high-performance analytical appliances will continue to grow as businesses exploit in-memory computing. An example is SAP’s HANA (High-Performance Analytic Appliance) that combines software components on hardware specifically designed to handle large volumes of data in real time. Fundamentally, because of the current evolving nature of data and analytics, businesses will want to gain access to the latest data and analytics appliances that can extract, transform, load data and are integrated with analytical applications.
Meanwhile, data will continue to grow, forcing smart businesses to go shopping for competent partners who can provide intelligence on demand, making Analytics-as-a-Service IT infrastructure clearly amongst the most visible current outsourcing trends.