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Sundar Ram, Vice President, Technology Sales Consulting, Oracle Corporation, Asia Pacific, tells N Geetha how big data is impelling IT managers to think of better storage management techniques
At this point of time, how relevant is big data to IT heads? How is it perceived?
For decades, companies have been making business decisions based on transactional data stored in relational databases. Beyond that critical data, however, is a potential treasure trove of non-traditional, less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. IT heads are grappling with tools to manage the data deluge, besides insufficient skills. While big data is not as obvious as ERP which has a direct proportion to the RoI, reduced capex and so on; it is not as quantifiable, but holds potential to be part of the business intelligence analysis.
Decreases in the cost of both storage and compute power have made it feasible to collect this data, which would have been thrown away only a few years ago. As a result, more and more companies are looking to include non-traditional yet potentially very valuable data with their traditional enterprise data into their business intelligence analysis.
IT heads can benefit from the fact that when big data is distilled and analysed in combination with traditional enterprise data, enterprises can develop a more thorough and insightful understanding of their business, which can lead to enhanced productivity, a stronger competitive position and greater innovation, all of which can have a significant impact on the bottom line. It will enable them to study the behavioural pattern across each market segment and work a cost-benefit analysis.
What are the top challenges in big data (operational, data characterisation, interpretation, data visualisation, relevancy and so on)?
The greatest challenge for IT managers is with regard to contextualising the technology and data to suit market intelligence to make it user friendly. Characterisation of data, given the technological hype and tools available is a big challenge. Lack of information architecture is also a challenge. While big data is not a challenge in itself, it can help them build a structure with the existing data.
For instance, IT managers can evolve their current enterprises data architecture to incorporate big data and deliver business value, leveraging the proven platforms to address their big data requirements.
Big data is adopted where there is enormous data flow and sectors including healthcare and telecom are likely to be the early adopters.
What kind of business requirements do you see for building a big data platform?
IT managers would need right tools to capture and organise a wide variety of data types from different sources to derive real business value from big data. Big data appliances come with features which can have hardware, software, storage and networking needs. Before looking for appliances, it is critical to understand what big data is all about. Traditional enterprise data, including customer information from CRM, transactional ERP data, web store transactions, and general ledger data comprises big data. Besides, machine-generated/sensor data including call detail records (CDR), web logs, smart meters, manufacturing sensors, equipment logs, trading systems data, etc. Data generated from social media platforms too gets categorised as big data. Big data revolves around volume, velocity, value and variety.
The infrastructure requirements in big data spans data acquisition, data organisation and data analysis. It is important to create a single framework to address all the three areas. NoSQL databases are critical to collect and store big data, particularly for the data structures that are scalable and frequently changing.
Organising data is the next step in big data management where IT managers could use Hadoop technology that allows large data volumes to be organised and to be kept on the original data storage cluster. Hadoop Distributed File System (HDFS) is a long-term storage system for web logs. From analysis standpoint the infrastructure required for big data to support deeper analytics, including statistical analysis and data mining and inventory is done from a smart vending machine which will dictate the product mix and replenishment schedule.
What innovations are happening around big that are driving down costs?
The first value proposition that the IT managers will think of is to rationalise the storage consumption and deploy robust solutions particularly given the increasing magnitude of internal users and customers. New technologies have emerged to address the IT infrastructure. Technologies like NoSQL are used to manage, secure RDBMS. Distributed file systems and transaction stores are primarily used to capture data. To get the most from NoSQL solutions and turn them from specialising, developer centric solutions and solutions for the enterprise, they must be combined with SQL solutions into a single proven infrastructure that meets the manageability and security requirements.
We encourage customers to use our big data appliance which comes with software and hardware engineered into one to address the challenge.
How will IT heads benefit by addressing big data issues in their organisation (in terms of their individual growth)?
The benefit that the IT heads observe is to go back to the business to tell how to streamline data growth and tame data deluge using big data appliance. IT managers conversation should no more be on which product or tool to deploy to manage storage, but what kind of SLAs should be worked out to address the data growth and big data.
According to industry reports, humans created 150 exabytes of data in 2005, and that number grew eight times to 1,200 exabytes by 2010. Similarly, as per industry estimates enterprise data is growing nearly 60 per cent per year (90 per cent of that being unstructured) and the average amount of data stored per company is 200 terabytes.
This flood of information creates a wealth of opportunities for businesses. For example, in the delivery of healthcare services, management of chronic or long-term conditions is expensive. Use of in-home monitoring devices to measure vital signs, and monitor progress is just one way that sensor data can be used to improve patient health and reduce both office visits and hospital admittance.
Manufacturing companies deploy sensors in their products to return a stream of telemetry. This telemetry also reveals usage patterns, failure rates and other opportunities for product improvement that can reduce development and assembly costs.
The proliferation of smartphones and other GPS devices offers advertisers an opportunity to target consumers when they are in close proximity to a store, a coffee shop or a restaurant. This opens up new revenue for service providers and offers many businesses a chance to target new customers.
Retailers usually know who buys their products. Use of social media and web log files from their ecommerce sites can help them understand who didnt buy and why they chose not to, information not available to them today. This can enable more effective micro customer segmentation and targeted marketing campaigns, as well as improve supply chain efficiencies.
Finally, social media sites of various business models requires a personalised experience on the web, which can only be delivered by capturing and using all the available data about a user or member.
IT managers should understand that the big data platform is engineered to explore a new chapter of data analytics which has the potential to generate business insights from different data sets changing the way organisations traditionally use information. It is a new application that can address storage management challenges.
How will the big data opportunity get addressed in the cloud environment?
In the cloud, big data refers to specific solution as it is broken down to smaller solutions. Big data is currently in the testing phase and not being considered as a cloud option.
What do you recommend IT heads to do to address big data related challenges?
There are a few things IT managers should prioritise.
a) Analyse and collate the pieces of data that holds value to them
b) Work out a strategy to manage this data with the existing information architecture
c) Experiment with the storage and other technologies in streamlining the data that can attract serious attention from the business groups
d) Assess organisational preparedness and availability of resources to manage the growing data given the emerging tools and technologies
e) Understand growing business needs and expansion plans before deploying new applications to address storage management requirements
There is a lot of buzz in the telecom, banking, insurance and the travel industries to look at big data applications as they grow in web presence and experience increased web traffic.
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