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Big Data Analytics: Exploring A Strategic Asset In Building Cyber Analytics

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Vishal Sinha, President and CIO, Tranzlease Holdings (I) Pvt. Ltd,,

TZL was established in 2006 in recognition of opportunities - a growing Indian automobile industry, a lifestyle seeking corporate executive and a true demand to have an automobile financing solution that reduces the overall cost of ownership. The company is on a mission to create an Automobile Lifestyle for the customers through innovative, cost effective, transparent financing & leasing solutions along with a complete range of related products/services on a tech enabled 360-degree solution platform.

In past more than two decades, the landscape of technology has changed completely and has opened new frontiers which no one ever thought of a decade back and what was thought, a decade back no-more exists; Big data Analytics has taken a prominent place in all business for it to survive.

With IoT devices connecting worldwide the sophistication of cyber security threats, and the attacks has also multiplied with the complexity of IT networks. Traditionally and technically, the technologies and security tools that have been used to mine data and prevent cyberattacks have been more reactive than proactive and secondly have also created a large number of false positives, creating inefficiencies and distracting from actual threats. What’s more these traditional tools do not have the bandwidth required to deal with the large volumes of information.

In comparison, the power of big data analytics has given give cyber security professionals the ability to analyze data from various data sources including data types and then respond in real time by not only able to gather information from a vast universe but it is also able to connect the dots between data, making correlations and connections that may have otherwise been missed. This increased efficiencies for cyber-crime professionals and casts a wider more reliable net when it comes to thwarting cyber-attacks.

Big data analytics comes out with a must-have component of any effective cyber security solution due to the need of fast processing of the high-velocity, high-volume data from various sources to discover anomalies and/or attack patterns as fast as possible to limit the vulnerability of the systems and increase their resilience. Even though many big data analytics tools have been developed in the

past few years, their usage in the field of cyber security warrants new approaches considering many aspects including (a) unified data representation, (b) zero-day attack detection, (c) data sharing across threat detection systems, (d) real time analysis, (e) sampling and dimensionality reduction, (f) resource-constrained data processing, and (g) time series analysis for anomaly detection.

Cyber Analytics
With the emergence of ‘Internet of Things’ and billions of connected devices has created an ever larger surface for cyber attackers to exploit, which requires more fast, accurate detection of those attacks to quantify. The developments in mobile computing, communications and mass storage architectures in the past decade have brought about the phenomenon of big data, which involves unprecedented amounts of valuable data generated in various forms at a high speed. The ability to process these massive amounts of data in real time using big data analytics tools brings along many benefits that could be utilized in cyber threat analysis systems. By making use of big data collected from networks, computers, sensors, and cloud systems, cyber threat analysts and intrusion detection/prevention systems can discover useful information in real time. This information can help detect system vulnerabilities and attacks that are becoming prevalent and develop security solutions accordingly.

Big data analytics comes out with a must-have component of any effective cyber security solution


Challenges: Becoming an analytics driver organization to create value however there are sets of challenges too in making the data move freely across the ecosystem as analytics is not a technology issue but strategy and operational one.

- Building the organization structure and governance framework to support driven decision making
- Analytics Security & Compliance
- Delivering actionable insights across the organization
- Developing the talent needed to convert data into business.

Impact of Analytics- just to understand the impact of how data has transformed our daily lives, look no further than how the automotive industry experience has changed and also of the car buyers. - When Cars were bought from dealerships directly locally with no other online digital channel sales available, the dealership channel used to recommend in the best interest basis which car they like and a large amount of their own opinion. Today, Leasing companies and car research content delivery services utilize a vast array of data points to generate recommendations.

By analyzing what was viewed, when, on what device (and even whether the content was saved, as well as user activities such as internet searches, and browsing and scrolling within a webpage, recommendations can be tailored for millions of customers in real time.

In nutshell, data is a strategic asset and its use has become key differentiator for competition and if managed strategically can change the way businesses are run and how an organization can compete, win & leveraging on the data. Big data will fundamentally change the way businesses compete and operate across industry and Cyber Analytics using big data analytics can exploit and explore the true potential to protect data and insights to data. Companies that invest in and successfully derive value from their data will have a distinct advantage over their competitors — a performance gap that will continue to grow as more relevant data is generated, emerging technologies and digital channels offer better acquisition and delivery mechanisms, and the technologies that enable faster, easier data analysis continue to develop.

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