Big Data is one of the hottest topics in the IT world currently and has attracted phenomenal attention from every quarter. While its definition and overall market size may be debated, there is unanimity on its being a definitive source of competitive advantage across all industries.
Data refers to any information that is of value to a business. Big data is data that is too large to process using traditional methods. It originated with large web companies who had problems trying to query very large data sets which were primarily loosely structured. Big data generally is known for loosely structured data which is often incomplete and also has Petabytes/exabytes of data, has billions of records, flat schemas and is often distributed data.
In yesteryears, there were only a few sources from which data originated. However, new age technology disruptions have led to a massive explosion in data – with new channels of generating data – mobile devices, meters, Social Media, Web logs to name a few. The rate at which voluminous and different forms of data is being generated is phenomenal.
Barun Lala, Director, Storage, HP India, says, “With the rise of big data fueled by digital content, mobile growth and compliance requirements, many organizations are struggling to retain unstructured data while ensuring rapid accessibility over the long term.
With the huge amount of data at their disposal, companies are realising the wealth of information that they can mine to gain insights into their customers, business processes etc., leading to greater demand for Business Intelligence and analytics services. Organizations will have the ability to not only harness data of all types as part of making proactive business decisions but also obtain more useful information for business insights, improve the fidelity of existing information through the process of validation, and improve time to decision making. “Big Data presents many possibilities for enterprises and today’s CIOs understand this and consider Big Data and Business Analytics a top priority,” says Rajesh Rege, Sr VIce Presdient - Data Centre, Cloud and Virtulaisation, Cisco India and SAARC.
According to a recent study done by Gartner, Big data currently has the most significant impact in social network analysis and content analytics with 45% of new spending each year. Currently, the factors driving the big data market are financial trading, analysis of online customer behavior, media research & social media. The skills, practices and tools currently viewed as big data solutions will persist, as leading organizations will have incorporated the design principles and acquired the skills necessary to address big data concerns as routine flexibility in the future.
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| Rajesh Rege Sr. VIce Presdient - Data Centre, Cloud and Virtulaisation, Cisco India and SAARC | Martin J. Wildberger Vice President, WW Information Management Development, IBM | Amit Luthra National Manager, Storage & Networking Solutions Marketing, Dell India | Abhay Koranne Associate Vice President - DWBI, Collabera |
Big data is becoming increasingly main stream as businesses realize its benefits, including improved operation efficiency, better customer experience, and more accurate predictions. However, companies are often challenged by the complexities of traditional server solutions. Big data solutions must enable high performance and scale as the business demands.
To meet these requirements, IT organizations should consider an architectural approach which integrates compute, storage, and network and can scale as the business demands. Cisco and its partners understand the importance of effective big data infrastructure, and are working with the leading big data to offer solutions that meet their demands..
CIOs have the responsibility of providing the right tools and infrastructure to enable analytics and business intelligence that will improve business strategy, performance and profitability of the enterprise. Traditionally, the volume of data available to organizations was smaller and more structured. This data was generated from within the enterprise through or financial transactions and was stored within the enterprise’s applications like their CRM or ERP systems. “With the popularity of social media, online banking and shopping and a host of mobile devices sending millions of packets of data every day, the volume and range of data now available to enterprises is immense. Enterprises now have the opportunity to use this data to gain business advantage more than ever before,” says Dell.
Traditional business analytics tools are ineffective in handling Big Data and new approaches that can process unstructured and semi structured data to harness this new opportunity have been developed. They include open source frameworks like Hadoop and NoSQL databases such as Cassandra and Accumulo. Hadoop is able to break up the immense mass of Big Data into smaller data packets and analyze them in parallel. Hadoop is also a cost effective approach to Big Data analytics.
Martin J. Wildberger, Vice President, WW Information Management Development, IBM, says, "We have been talking about Big data for a number of years we have been just recognised for having the leadership platform for Big Data and reason for that is that we look at Big Data in a holistic manner. Thanks to our holistic view of the breadth and depth we are the only platform that can serve taking into scalability, manageability and performance into account enabling us to expand analytics to encompass Big Data, information streams, and structured data in Data Warehouses."
Big Data and BI strategy
Today, enterprises want to be smart. Managing data growth is the number two priority for IT organizations over the next 12-18 months. According to a recent survey by MIT, companies that inject Big Data and analytics into their operations show productivity rates and profitability that are 5% to 6% higher than those of their peers. According to Cigniti, “Rapid adoption of social media, increased usage of analytics (based on trends / patterns), Informed decision making have been the key business drivers for Big Data. Consumers like to have access to real-time information most of the time and smart phone usage has increased the demand an d need for this information.”
Collabera says, “None of the traditional BI tools have the ability to work with unstructured data or large volumes. Hence, the landscape is undergoing a sea change. Big data requires the ability to not only process faster, but process a wide variety of data – both structured and unstructured - and also the ability to store huge volumes of data. New tools are fast emerging to address these challenges.
The capture, integration, aggregation, storage and analysis processes of an IT organization have to change due to Big Data. The traditional BI tools have to be augmented with new-gen analytics tools. The decision to have cloud based analytics services versus on premise BI will have to be taken based on the specific priorities of each enterprise.
Business Intelligence that is secured through Big Data analysis can provide accurate insights into customer and market dynamics, giving the enterprise a competitive advantage in the marketplace. Predictive analytics enables firms to be more nimble towards future changes in markets and customer behavior. Big Data enables enterprises to listen and respond to their customers and potential customers, making it an essential tool to enterprise success.
Big Data analytics is a very crucial component of Big Data solutions. Effectively managing old and new sources and acquiring the tools that can interrogate and make sense of the data is a part of the equation. Organizations need to get a good amount of ROI for their Big Data solutions and the vendors are an integral part in helping organizations get sophisticated and reliable results out of the tons of data generated. If organizations are able to see the need for Big Data and data analytics in terms of input vs. output, the growing opportunities are huge.
Mu Sigma says, “Big Data analytics can bring deep insights and new perspectives such as better risk management, improving marketing campaigns effectiveness and making supply chain more robust.”
Cigniti says, “The approach and the changes that Big Data brings in can be defined by associating with what matters to the line of business you are in.”
Conventional analytics have given away to segmented, powerful, targeted, vertical specific tools that you can leverage through Big Data. Analytics can be broadly looked up in 4 categories- Descriptive Analytics, Diagnostic Analytics, Prescriptive Analytics and Predictive Analytics.
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| Raj Neravati Chief Operating Officer at Cigniti Technologies |
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| Deepinder Dhingra Head of Products & Strategy, Mu Sigma |
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| Barun Lala Director, Storage, HP India |
Business Intelligence strategies are no more being driven by conventional data ware housing practices. The new ‘normal’ in BI strategy is the ability to ensure intelligent cataloguing of all the data that is generated form multivarious data sources and drawing real time inferences to accomplish objectives. Companies have realized that Smart Data = Big Data + context + inference + declaratively interactive visualization. “Companies are employing Data Scientists (Eg: LinkedIn) to implement big data with the need to model & finally the need to test. Here is where companies like Cigniti help their clients with point solutions on Big Testing,” says Cigniti.
SMBs Leveraging Big Data
Realistically, a Big Data situation occurs largely in larger organizations due to their internal complexity and scale of operations. It may not be a problem for SME. They are more likely to be seeking solutions for issues like setting up IT infrastructure. However, they can make use of Big Data to get the data foundation layer right first as their business grows.
The approach to address the issues of Big Data for an SMB, will be pretty much the same as for any large organization. Just because the organization is of small scale and size does not necessarily implies that it cannot land into Big Data troubles or they cannot use Big Data for their competitive advantages. “What is important is to create the groundwork for tomorrow because they need the ability and expertise to implement big data strategies if they want to cut costs and improve profitability for their organization. The way data is increasing and open source tools are mushrooming, SMB’s need to think about Big Data as the new essential for innovation and profitable growth,” says Mu Sigma.
Collabera says, “Big data might not be a matter of immediate concern for many SMBs, though there could be a few exceptions. For some, the traditional data store and BI tools would do. However, the power that the new-gen tools bring in from a processing and storage perspective can be harnessed by SMBs to further their business objectives.” An SMB should start with a well thought out Big Data strategy, investing in on-premise storage or BI tools at the beginning and evaluate how things go. They can use cloud based storage and BI services as well. One other aspect that an SMB needs to focus on is to manage the data better.
Open source software (SaaS), cloud based hosting are few catalysts for Big Data adoption among the SMB sector.
Big Data analytics can bring deep insights and new perspectives such as better risk management, improving marketing campaigns effectiveness and making supply chain more robust.
SMB’s can take significant advantage of Big Data. Big Data actually creates a level playing field for SMBs to compete with large enterprises. Big Data analytics also enables SMBs to improve their overall customer experience by performing “social listening” - or collecting unstructured data insights from social media and pulling out specific comments and conversations that directly affect their line of business. Cigniti says, “SMBs with a meticulously tested big data application will ensure the investments on the project yield the right set of analytics to make insightful decisions for a successful business. SMBs cannot afford to compromise on the cost of quality in particular to the data under scan.”
Indian Scenario
Healthcare where increasingly organizations (both private and public sector) are thinking about st oring Big Content (electronic health records, medical images, etc.) for many decades, making them available across organizational boundaries (such as hospitals) and data centers. Additionally, the capability to use Big Analytics to gain insight into health trends and quickly analyze large data sets is gaining traction. Financial Services where the ability to quickly and completely analyze past transactions for trend detection and forecasts is core to financial success, as well as the processing and storage of documents in accordance with retention periods and processing mandates
HPC and Media & Entertainment are very data-intensive verticals with a dramatic data growth every year. In these verticals the ability to leverage Big Bandwidth to quickly ingest and process large amounts of data is critical, as is the long term retention of compute results and media content
In India, the awareness about Big Data is gaining momentum. The verticals that include Healthcare, Financial Services, HPC and media & entertainment would be the early adopters.
Verticals like BFSI, Retail, Media, and government sectors will adopt Big Data immediately owing to the enormous data flow, while sectors such as healthcare and telecom are likely to be among the early adopters before most verticals adopt Big Data solutions.
Martin of IBM says, "Industries people see the potential and excitement about how do we exploit the new source of data. We are working with a number of companies in different industry like banking, financial services and Telcos in India. These companies are looking at how to take advantage of the big data platform to drive competitive differentiation."
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