BFSI VISION | Analytics


Srinivas Tadigadapa
Director, Enterprise Solution Sales, Intel South Asia

Technology offering for Big Data Analytics

The explosion of big data is testing the capabilities of even themost advanced analytics tools. The IT field is constantly challenged by the sheervolume, variety, and velocity of this flood of complex, structured,semi structured, and unstructured data—which also offers organizations exciting opportunities to garner richer, deeper, and more accurate insights into their business.

Traditional systems are unable to cope cost-effectively—if at all—with new dynamic data sources and multiple contexts for big data. Emerging technologies such as the Hadoop* framework represent completely new approaches to capturing, managing, and analyzingbig data. Big data challenges plus new technologies are causing a paradigm shift that is driving organizations to re-examine their IT infrastructure and analytics capabilities.

As the use of sensors and devices as well as intelligent systems continues to expand the potential to gain insight from the flood of data from these sources becomes a new and compelling opportunity. Businesses that can harness the power of big data will unlock its value to the organization will outperform their competitors with greater capabilities to innovate creatively and solve complex problems whose solutions have been out of reach in the past.

As the use of sensors and devices as well as intelligent systems continues to expand the potential to gain insight from the flood of data from these sources becomes a new and compelling opportunity. Businesses that can harness the power of big data will unlock its value to the organization will outperform their competitors with greater capabilities to innovate creatively and solve complex problems whose solutions have been out of reach in the past.

Organizations are increasingly asking for a common platform to enable transformation to a Software Defined Infrastructure (SDI), optimizing the use of pooled resources through orchestration. As the global technology shift drives Enterprises worldwide will move from a hardware driven infrastructure to a Software Defined Infrastructure which is equipped to power a broad set of workload functions such as Data Analytics and cloud-based services. The Intel Xeon® E5 v3 processor family will be used in servers, workstations, storage and networking infrastructure offering industry leading capabilities to enterprises as well as simultaneous back-end processing for IoT functions. It will also bring about a holistic development in the automation of government records.The enabling of G2C service in a vast country like India will present a fantastic opportunity for Big Data Analytics to address this niche market.

Factors should banks focus on in BDA exercise

The application of Big Data analytics in the banking and financial services industry has been around for quite a while now. Banks have begun putting data warehouses in place and have also started investing in technology that would help it make sense of the massive troves of unstructured data captured by its information technology (IT) systems.

Banks that are offering loans to customers are now looking at Big Data analytics as a tool to generate more revenue as they now receive valuable insights on customers and markets.

After the initial data warehouse placements, banks then integrate the analytics engine with every aspect of the core operations to extract valuable customers perspectives that would help improve revenue productivity and lower the risk of being exposed to fraud.

With the analytics engine already in place, they can track minute aspect of a typical customer's financial habits. Big Data Analytics tools also give the bank fresh insights into their customer's personal habits, allowing it to customize and promote its offers accordingly.

Adding on to the merits of using analytics banks are now also able to keep an accurate track of credit ratings and history of customers and can hand out loans accordingly. The quantifiable value of analytics has now become rather easy to determine.

Today we are seeing that banks are focusing on big data with an emphasis on an integrated approach to customers and internal operations.

How can a right technology vendor smoothen the process

The true payoff for enterprises is in investing in big data solutions that analyze increasingly larger volumes of complex and diverse forms of data and provide real-time insights that can be used to drive results. Intel is offering Big Data through open data management and analytics software platforms including the Intel Distribution of Apache Hadoop* software (Intel® Distribution) and the Intel Enterprise Edition for Lustre* software and has identified multiple routes to market for its big data solutions through system integrators (SI), independent software vendors (ISV) original equipment manufacturers (OEM) and training partners

Intel is ready to foster the big data ecosystem in India through its broad collaboration with partners by building partnerships with various India-based ISVs across various business segments including BFSI, Manufacturing, Education, Retail, Telecom, Healthcare, etc.

Trends seen in Big Data Analytics across the globe

Some of the Big Data analytic trends that we believe willemerge are associated in parallel with consumer trends and technological innovationsthat willreshape how companies are able to make precise data-driven decisions.

Data Visualization will be at the forefront

Data visualization is strongly expected to make data analytics more accessible by 2015. Visual analytics will allow business users to their ask their prepared data sets a series interactive questions and receive immediate visual responses, which will makes the entire process all the more engaging. This trend will democratize access to data and foster a strong data analysis culture wherein business users will look for data and perform visual analysis initially before proceeding to making informed decisions.

Mobile Data will drive analytics

Smartphones and tablets have fundamentally redefined traditional consumer habits. Mobile internet is predicted to take over the reins from desktop internet according to Microsoft Tag. According to GSMA findings, the average monthly consumer spending on mobile content and services in emerging markets reaches a peak of almost $1 billion, which presents an additional significant marketing and data analytics opportunity. This essentially means that the top priorities for companies will be defining mobile metrics that matter, understanding mobile technology, the data creation process and consequently assimilating and analyzing mobile data.

Analytics in the Cloud

Innovations, such as the likes of the cloud data warehouse platforms will establish firm footing and set new benchmarks in self-service BI, enabling scalable, fast, and secure solution at affordable prices. The robustness in the process of this platform will allow businesses to save considerably on infrastructure design, setup, and management costs. It will also free up more resources to be allocated on issues that matter most for their customers, thereby gaining by acting on the received business insights.

Predictive Analytics Takes Center Stage

For decades, companies have churned out data platforms and analytics infrastructure with a significant emphasis on hindsight: look-back reports that help businesses check their rear view mirrors. Today's scenario demands a paradigm shift from that earlier notion as enterprises need to start developing insights and foresights simultaneously. With better insights and a forward-looking predictive view, businesses are less reactive and are able to be more proactive to address their outcomes in an efficient manner. More importantly, CIOs have now started thinking about their predictive analytic needs even as they build today's infrastructure and explore newer technologies such as Hadoop to manage their unstructured data and co-exist with their traditional data stores. The quick wins provided by data visualization so far, and the increasing appetite for business users to explore data for decision making, provide the platform for predictive analytics to significantly gain ground in 2014.

Internet of Things

The year 2013 saw the rise of a revolution in the field of wearable computing technology - Google Glass, Smart watches, activity monitors, etc. Although we are still some distance away from mass adoption, we expect to see much more activity in this field by 2014. Companies that do a great deal in product design and development will emerge as the early winners as they drive adoption through innovative marketing strategy. Additionally, as more people use these technologies, companies will be able to monetize the data they collect through wearable devices. For example, makers of these devices will have access to activity and demographic data that could prove valuable for health insurance companies. For businesses purposes, IoT offers a unique opportunity to develop new services, enhance productivity and efficiency, improve real-time decision making capabilities, solve critical problems using unique algorithms, and effectively enhancing new consumer experiences while consistently pleasing the existing customer base. Given the strong focus of the new government in India to build Smart Cities, critical areas like IoT will undoubtedly become a ground reality and manifest itself as an irresistible opportunity for the development of new technologically defined ecosystems that cater to the specific and general needs of governments and citizens' alike.

Key success factors in successful deployment of Big Data Analytics

The critical factors resulting in a successful deployment of big data analytic projects can be divided into three broad segments, organizational factor which mandates a clear and concise mission & vision case highlighting its purpose. The second being the technological factor which entails presence of suitable technical framework and infrastructure, availability of data to be integrated in real time with other systems, presence of strong security measures along with a high degree of flexibility in process operations.

This flexibility must also be imbibed within the system's ability to adapt to new business requirements while simultaneously supporting new variations of data warehousing and event processing scenarios.

The third segment is the area of performance, which sets benchmarks upon the quality of systems and the information they process, the time required to churn out measurable responses out of ambiguous data and lastly measures its cost efficiency The success of the deployment of Big Data Analytics can be attributed to the positive value an organization obtains through its Bigdata analysis investments. Depending on the sector the organization operates in, measurable indicators can include information quality, customer satisfaction, cost, time and most importantly return on investment. Whereas return on investment can be based on tangible as well as intangible, but quantified assets

Managing mission-critical assets requires a reliable assessment of the current and future operational conditions for that asset. Intel® Decision Solutions: Trend Analytics Software addresses these predictive maintenance challenges. By enabling remote monitoring, trending, and diagnostics, it can help organization successfully make the right operations and maintenance decisions at the right time.

Trends seen in the evolution of Big Data Analytics

Big data has long been deemed a game changer. While most of the momentum around big data today is still focused around social media sources. Intel believes that realizing upon the promise of big data analytics must also include a way to harness the exponential potential of big data from intelligent systems and sensors.

Big data—a market that IDC has forecasted to surge at a 40 percent compound annual growth rate from $3.2 billion in 2010 to $17 billion in 2015—presents a formidable new frontier in which data sets can grow so large that they become intimidating albeit slightly embarrassing to work with by using traditional database management tools. Therefore, the need for new tools, frameworks, hardware, software and services to handle this emerging issue represents a huge market opportunity yearning to be addressed.

The tempo of innovation in this space more recently has been a combination of massive increases in the amount of data itself and a desire among enterprises and governments to use that data for something useful. So there are ongoing discussions on how to get more cost effective in managing and mining the data, for example governments, telcos, banks etc. They are looking for answers to questions like what economic benefit are they getting by keeping this data or how does that help in building insights about customers or users or communities.

Organizations are developing intellectual property around building software engines to support complicated analytics that can be delivered over the web. And Intel helps standardize the plumbing that sits underneath those things.