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5 Trends Shaping the Future of Data Analytics

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5 Trends Shaping the Future of Data Analytics

Data Analytics is popular. The future of data science and analytics is bright and happening. Terms like ‘artificial intelligence’ and ‘machine learning’ are taking the world by storm.

Annual demand for the fast-growing new roles of data scientist, data developers, and data engineers will reach nearly 700,000 openings by 2020, says Forbes, a leading business magazine.

 

Last year, at the DataHack Summit Kirk Borne, Principal Data Scientist and Executive Advisor at Booz Allen Hamilton shared some slivers of knowledge in the illuminating field of data science. He believes that the following trends will shape up the world of data analytics, and we can’t agree more.

Dive down to pore over a definitive list – thank us later!

Internet of Things (IoT)

Does IoT ring any bell? Yes, it does, because it’s nothing but evolved wireless networks. The market of this fascinating new breed of tech is expected to grow from $170.57 billion in 2017 to $561.04 billion by 2022 – reasons being advanced analytics and superior data processing techniques.

Artificial Intelligence

An improved version of AI is Augmented Intelligence – instead of replacing human intelligence, this new sophisticated AI program largely focuses on AI’s assistive characteristic, enhancing human intelligence. The word ‘Augmented’ stands for ‘to improve’ and together it reinforces the idea of amalgamating machine intelligence with human conscience to tackle challenges and form relationships.

Augmented Reality

Look forward to better performances and successful models? Data is the weapon of all battles. Augmented Reality is indeed a reality now. The recent launch of Apple ARkit is a pivotal development in bulk manufacturing of AR apps. The power of AR is now in the fingertips of all iPhone users, and the development of Google’s Tango is an added thrust.

Hyper Personalization

#KnowYourCustomer, it has become an indispensable part of today’s retail marketing; the better you know your customers, the higher are the chances of selling a product. Yes, you heard that right. And Google Home and Amazon Echo is boosting the ongoing operations.

Graph Analytics

Mapping relationships across wide volumes of well connected critical data is the essence of graph analytics. It’s an intricate set of analytics tools used for unlocking insightful questions and delivering more accurate results. A few use cases of graph analytics is as follows:

  • Optimizing airline and logistic routes
  • Extensive life science researches
  • Influencer analysis for social network communities
  • Crime detection, including money laundering

 
Advice: Be at the edge of data accumulation – because data is power, and data analytics is the power-device.

Calling all data enthusiasts… DexLab Analytics offers state of the art data analytics training in Gurgaon within affordable budget. Apply now and grab amazing discounts and offers on data analyst course.

 

The article has been sourced from – yourstory.com/2017/12/data-analytics-future-trends

 

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How Aspiring Data Scientists Should Choose a Suitable Programming Language for Data Science

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How Aspiring Data Scientists Should Choose a Suitable Programming Language for Data Science

Data science is a fascinating and one of the fastest growing fields in the world to work in. This is why it’s becoming increasingly popular for data scientists to consider the potentials of programming languages-they form an integral part of data science.

Possessing incredible skills of programming instantly pumps up the chances of bagging a high-profile data science job, whereas the novices, who have never studied programming in their entire life have to struggle hard.

However, this is not all – only a sack of all-round programming skills won’t help you grab the sexiest job of 21st century, there are several things to consider before you set off on becoming a successful data scientist. And they are as follows:

Generality

For a true blue data scientist, it’s not enough to possess encompassing programming skills but also the aptitude for crunching numbers. Remember, a data scientist’s day is largely spent on sourcing and processing raw data for the purpose of data cleaning – no amount of smart set of programming languages or machine learning models would be of any help.

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Specificity

In advanced data science, learning knows no bounds – each time you get to reinvent something new. Learn to ace a wide array of packages and modules available in a chosen language. However, the extent of the use and application is subject to the domain-particular packages you are working on.

Performance

In few cases, optimizing the performance of the codes is essential, especially when tackling huge volumes of crucial data. Compiled languages are normally faster as compared to interpreted ones; in the same way, statically typed languages are more fail-proof than dynamically typed. As a result, an apparent trade-off exists against productivity.

With all these in mind, it’s time to delve into the most popular languages used in the field of data science – let’s start with R – it’s the most powerful open source language used for a gamut of statistical and data visualization applications, including neural networks, advanced plotting, non-linear regression, phylogenetics and lot more.

Next, we can’t help but brag about an excellent all-rounder – Python – a top notch programming language choice for all types of data scientists, seasoned and freshers. A large chunk of the data science process revolves around the cutting edge ETL process – this makes Python a universal language to excel at. Google’s Tensorflow is an added bonus point.

Lastly, SQL tops rank as a leading data processing language instead of being just an advanced analytical tool. Owing to its longevity and efficiency, SQL is deemed to be one of the most powerful weapons that modern data scientist should know of.

Parting Thoughts

In the end of the discussion, we now have a set of languages to consider for excelling data science – what you need to do is comprehend your usage requirements and compare generality, specificity and performance factors. This will help you surge towards a successful career minus the complexities associated.

DexLab Analytics offers top of the line Data Science Courses in Delhi for data enthusiasts. If you are interested in a data analyst course in Noida, drop by this esteemed institute and navigate through our in-demand courses.

 

The blog has been sourced from – 

https://medium.freecodecamp.org/which-languages-should-you-learn-for-data-science-e806ba55a81f

https://towardsdatascience.com/what-programming-language-should-aspiring-data-scientists-learn-875017ad27e0

http://bigdata-madesimple.com/how-i-chose-the-right-programming-language-for-data-science

 

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How Data Science Is Getting Better, Day by Day?

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HOW DATA SCIENCE IS GETTING BETTER, DAY BY DAY?

In the latest Star Wars movie, the character of Rose Tico – a humble maintenance techie with a talent for tinkering is relatable; her role expands and responsibilities increase as the movie gets going, just like our data scientists. A chance encounter with Finn puts her into the frontlines of action, and by the end of the movie, she’s flying ski-speeders in the new galactic civil war, one of the most critical battles in the movie – with time, her role becomes more complex and demanding, but she never quivers and embraces the challenges to get the job done.

A lot many data scientists draw similarities with Rose’s character. In the last 5 years, the job role and responsibility of data analysts has undergone an unrecognizable change – as data proliferation is increasing in capacity and complexity, the responsibility is found shifting base from dedicated consultants to cross-functional, highly-skilled data teams, proficient enough in integrating skills together. Today’s data consultants need to complete tasks collaboratively to formulate trailblazing analysis that let businesses predict future success and growth pattern, effectively.

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Quite conventionally, the intense role of prediction falls on the sophisticated crop of data scientists, while business analysts are more oriented towards measuring churn. On the other hand, intricate tasks, like model construction or natural language processing are performed by an elite team of data professionals, armed with strong engineering expertise.

Said differently, the emergence of data manipulation languages, such as R and Python is surging – owing to their extensive usage and adaptability, businesses are biased towards implementing these languages for advanced analysis. Drawing inspiration from Rose’s character, each data scientist should adapt to newer technology and expectations, and enhance expertise and skills that’s needed for the new role.

However, acing the cutting edge programming languages and tools isn’t enough for the challenge – today, data teams need to visualize their results, like never before. The insights churned out of advanced machine learning are curated for consumption by business pioneers and operation teams. Thus, the results have to be crisp, clear and creatively presented. As a result, predictive tools are being combined with effective capability of Python and R with which analysts and stakeholders are quite familiar.

The whole big data industry is changing, and the demand for skilled big data analysts is sky-rocketing. In this tide of change, if you are not relying on advanced data analysis tools and predictive analytics, you are going to lag behind. Companies that analyze data, boost decision-making, and observe social media trends – changing with time – will have immense advantages over companies that don’t pay attention to these crucial parameters.

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No second thoughts, it’s an interesting time for data aspirants to make significant impacts in the whole data community and trigger fabulous business results. For professional training or to acquire new skills – drop by DexLab Analytics – their data Science Courses in Noida are outstanding.

The blog has been sourced from –  dataconomy.com/2018/02/whole-new-world-data-teams

 

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Here’s How Technology Made Education More Enjoyable and Interactive

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Here’s How Technology Made Education More Enjoyable and Interactive

Technology is revamping education. The entire education system has undergone a massive change, thanks to technological advancement. The institutions are setting new goals and achieving their targets more effectively with the help of new tools and practices. These cutting edge methods not only enhances the learning approach, but also results in better interaction and fuller participation between teachers and students.

The tools of technology have turned students into active learners; they are now more engaged with their subjects. In fact, they even discover solutions to the problems on their own. The traditional lectures are now mixed with engaging illustrations and demonstrations, and classrooms are replaced with interactive sessions in which students and teachers both participate equally.

Let’s take a look at how technology has changed the classroom learning experience:

Online Classes

No longer, students have to sit through a classroom all day. If a student is interested in a particular course or subject, he or she can easily pursue degrees online without going anywhere. The internet has made interactions between students and teachers extremely easy. From the comfort of the home, anyone can learn anything.

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Free educational resources found online

The internet is full of information. From a vast array of blogs, website content and applications, students as well as teachers can learn anything they desire to. Online study materials coupled with classroom learning help the students in strengthening their base on any subject as they get to learn concepts from different sources with examples and practice enough problems. This explains why students are so crazy for the internet!

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Webinars and video streaming

The facilitators and educationists are nowadays looking up to video streaming to communicate ideas and knowledge to the students. Videos are anytime more helpful than other digital communications; they help deliver the needful content, boosting the learning abilities among the learners, while making them understand the subject matter to the core. Webinars (seminars over the web) replaces classroom seminars; teachers look up to new methods of video conferencing for smoother interaction with the students.

Podcasts

Podcasts are digital audio files. Users can easily download them. They are available over the internet for a bare subscription fee. It’s no big deal to create podcasts. Teachers can easily create podcasts that syncs well with students’ demand, thus paving a way for them to learn more efficiently. In short, podcasts allow students a certain flexibility to learn from anywhere, anytime.

Laptops, smartphones and tablets

For a better learning experience overall, both students and teachers are looking forward to better software and technology facilities. A wide number of web and mobile applications are now available for students to explore the wide horizon of education. The conventional paper notes are now replaced with e-notes that are uploaded on the internet and can be accessible from anywhere. Laptops and tablets are also used to manage course materials, research, schedules and presentations.

No second thoughts, by integrating technology with classroom training, students and teachers have an entire world to themselves. Sans the geographical limitations, they can now explore the bounties of new learning methods that are more fun and highly interactive.

DexLab Analytics appreciates the power of technology, and in accordance, have curated state of the art Data Science Courses that can be accessed both online and offline for students’ benefit. Check out the courses NOW!

 

The article has been sourced from – http://www.iamwire.com/2017/08/technology-teaching-education/156418

 

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How Blockchain Technology is Transforming these Four Popular Industries

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How Blockchain Technology is Transforming these Four Popular Industries

Blockchain technology is the next big thing. It is defying industry norms and altering the manner in which industries implement new projects. The decentralized nature of blockchain technology is the key to its success. Blockchain is transforming every organization through its secure and decentralized protocols, protected peer-to peer applications, and a new approach towards distributed management.

Here are some everyday industries that blockchain technology is revamping.

  • Finance:

There are all kinds of opinions regarding how cryptocurrency is impacting macroeconomics pertaining to the financial sector. The rapidly increasing demand for Bitcoin signals a flourishing future for cryptocurrency. In 2017, ICOs (Initial Coin Offerings), which are means of crowd funding centered on cryptocurrency, raised more money than venture capital investments. Cryptocurrencies, like Bitcoin, Ethereum and Ripple are improving their speed for processing transaction fees, and will be able to contend with speed of transaction for credit card companies in the near future. Bitcoin permits people to transfer money across borders instantaneously and at low costs. Many banks, such as Barclays, are set to use blockchain technology to facilitate speedier business procedures.

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  • Cloud Computing:

The evolution of cloud has outmoded hard drives, which was the popular choice for transferring files from one computer to another, even a few years ago. Blockchain-based companies, like Akash, want to seize this opportunity and create an open market place where cloud computing costs are determined by demand and supply, instead of centralized, fixed prices. Most large-scale data centers depend on idle computing power. Akash Network makes idle server capacity available for cloud deployments. This system enables users to ‘’rent’’ idle computing power and providers to generate revenue from their idle power. Developers specify their deployment conditions in a file that is posted on the Akash blockchain. Providers capable of fulfilling these conditions bid on it. Low bid wins; after this parties go off chain to allocate workload in Docker containers. Akash tokens are then transferred from tenant‘s wallet to provider’s wallet.

  • Online Gaming:

The online sports industry is embracing the blockchain technology. An increasing number of developers in the world of e-Sports are employing blockchain technology and cryptocurrencies. Leading fantasy sport companies, like MyDFS, permit their users to create virtual arrays of real players and obtain winnings through tokens. In-app purchase is the newest monetization model for Smartphone app games. Blockchain technology is also advantageous for e-Sports betting platforms. The tech constructs a secure environment for low fee betting that is free from the control of a central party.

  • Decentralized Governance:

One of the most famed features of blockchain is decentralization. The thought of decentralized, autonomous organizations is no doubt very fascinating, but they are very difficult to establish. A hierarchical structure, where one person or group tends to dominate, is very natural. However, new and advanced frameworks are facilitating decentralized platforms to function effectively. An example of such a framework is DAOstack, which is striving to build a platform that enables collectives to self-organize around similar goals and interests. It is a platform that authorizes emerging organizations to select suitable governance model that will work for them and execute the same through DAOstack’s technological protocol. DAOstack’s founding principle is collaboration- it aims to provide a setting where goals of individuals can work in harmony with goals of a group.

The ‘’blockchain boom’’ is driving breakthroughs for a range of industries. This is just the beginning, though. As this tech evolves, it will enable rapid progress across every industry.

To read more blogs on emerging technologies, follow DexLab Analytics; it is a premier institute providing data science certification courses in Delhi. Do take a look their data analytics certification courses.

 

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Microsoft Introduces FPGA Technology atop Google Chips through Project Brainwave

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Microsoft Introduces FPGA Technology atop Google Chips through Project Brainwave

A Change Is In the Make – due to increasing competition among tech companies working on AI, several software makers are inventing their own new hardware. A few Google servers also include chips designed for machine learning, known as TPUs exclusively developed in-house to ensure higher power and better efficiency. Google rents them out to its cloud-computing consumers. Of late, Facebook too shared its interest in designing similar chips for its own data centers.

However, a big player in AI world, Microsoft is skeptical if the money spent is for good – it says the technology of machine learning is transforming so rapidly that it makes little sense to spend millions of dollars into developing silicon chips, which could soon become obsolete. Instead, Microsoft professionals are pitching for the idea of implementing AI-inspired projects, named FPGAs, which can be re-modified or reprogrammed to support latest forms of software developments in the technology domain.  The company is buying FPGAs from chip mogul, Intel, and already a few companies have started buying this very idea of Microsoft.

This week, Microsoft is back in action with the launch of a new cloud service for image-recognition projects, known as Project Brainwave. Powered by the very FPGA technology, it’s one of the first applications that Nestle health division is set to use to analyze the acuteness of acne, from images submitted by the patients. The specialty of Project Brainwave is the manner in which the images are processed – the process is quick as well as very low in cost than other graphic chip technologies used today.

It’s been said, customers using Project Brainwave are able to process a million images in just 1.8 milliseconds using a normal image recognition model for a mere 21 cents. Yes! You heard it right. Even the company claims that it performs better than it’s tailing rivals in cloud service, but unless the outsiders get a chance to test the new technology head-to-head against the other options, nothing concrete can be said about Microsoft’s technology. The biggest competitors of Microsoft in cloud-service platform include Google’s TPUs and graphic chips from Nvidia.

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At this stage, it’s also unclear how widely Brainwave is applicable in reality – FPGAs are yet to be used in cloud computing on a wide scale, hence most companies lack the expertise to program them. On the other hand, Nvidia is not sitting quietly while its contemporaries are break opening newer ideas in machine learning domain. The recent upgrades from the company lead us to a whole new world of specialized AI chips that would be more powerful than former graphic chips.

Latest reports also confirm that Google’s TPUs exhibited similar robust performance similar to Nvidia’s cutting edge chips for image recognition task, backed by cost benefits. The software running on TPUs is both faster and cheaper as compared to Nvidia chips.

In conclusion, companies are deploying machine learning technology in all areas of life, and the competition to invent better AI algorithms is likely to intensify manifold. In the coming days, several notable companies, big or small are expected to follow the footsteps of Microsoft.

For more machine learning related stories and feeds, follow DexLab Analytics. It is the best data analytics training institute in Gurgaon offering state of the art machine learning using python courses.

The article has been sourced from – https://www.wired.com/story/microsoft-charts-its-own-path-on-artificial-intelligence

 

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How American Express Uses Data Analytics to Promote a Data-Driven Culture

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data analytics training institute

Since 2010, American Express, with an encompassing database crossing over 100 million credit cards accounting for more than $ 1 trillion in charge volume annually, is harnessing the power of big data. Undeniably, it resulted in incredible improvements in speed and performance.

In the last four decades, the entire financial services industry has undergone a massive change, notably in the spheres of:

Electronic payments – Online payments, comprising credit and debit cards have dramatically increased over cash, globally.

E-commerce – An excessive reliance on smartphones and internet have boosted E-commerce capabilities manifold times.

With an increasing interaction between company and customers, the latter’s online and offline identity is being collaborated for an encompassing 360-degree view. This eventually drives innovation in product designing and marketing.

Formulating a Data-Driven Culture

Data analytics is like the bull’s eye of effective marketing, and servicing and risk management. Data curation and management is now a prerequisite for competitive excellence.

Since its inception, American Express flaunts transformation: the company has transformed itself from being a trivial freight forwarding business to a top notch player in payments and customized service industry. Over the years, the working mechanism of the firm has changed dramatically, and today, it is #1 small business card issuer in the whole of the US.

No matter, while the company strives to evolve, its core values remain somewhat same. Keeping their customers above anything else and behave like a good citizen are two core values of American Express that are beyond alterations. To become a successful data-driven organization, they believe in investing on technology, analytics, along with human talent, emphasizing on a proper synthesis between technology and human cognition to trigger robust growth and future success.

How American Express Stays Relevant and Fresh?

Risk 2020 – American Express envisions how an economy or marketplace might look like after a few years, and in the process, assesses the risks to combat to address the weaker issues in the economy. A comprehensive approach, including cloud, deep learning, mobile computing and AI is the solution.

Cornerstone – This is an encompassing, global big data ecosystem. The data is stored and shared with global potentialities across trusted sources. In any organization, data is the centre of attraction, and the consultants at American Express recognize the essence of innovation lies at company’s DNA and not somewhere on the top.

The data-driven culture in American Express is simple, natural and nuanced. A huge data base is created, from acquisition to customer management, which eventually needs to be shared with third parties and partners to derive insightful conclusions for better customer experience and risk assessment. “At American Express, we take our responsibility to serve customers and the public seriously, always ensuring that solutions are best-in-class and valuable to our customers,” says Ash Gupta, president, Global Credit Risk & Information Management, American Express.

“American Express’ closed-loop data allows us to analyze a large volume of real spending that can help marketers across a range of industries connect with customers and provide unique value,” he further adds.

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To know more about data-driven customer experience, visit DexLab Analytics, a premier data analyst training institute in Delhi. They offer a plethora of data analyst training courses for interested candidates.

 

The blog has been sourced from:

https://www.forbes.com/sites/ciocentral/2018/03/15/how-american-express-excels-as-a-data-driven-culture/#5c5ed1a81635

https://digit.hbs.org/submission/american-express-using-data-analytics-to-redefine-traditional-banking/

 

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Facial Recognition Technology: Where Opportunities are Endless and Science is Terrific

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Facial Recognition Technology: Where Opportunities are Endless and Science is Terrific

We are on the verge of the Fourth Industrial Revolution – where massive amounts of texts, tweets, photos, videos, status updates, GPS coordinates, reposts and clickstreams are being pumped out into the digital universe. This data is like the food for colossal artificial intelligence.

If we talk about resources, the ocean that AI-induced data has filled up is nothing if compared to California gold rush, Texas Oil boom or similar events. Huge amounts of data are clogging the digital space all over. Algorithms, based on AI are driving innovation in every field of work, right from products to services, and the more data you possess, the more accurate the algorithm is expected to be. As a result, collection and analysis of big data have become a prime focus of companies, big and small.

Introducing Deep Learning

But how does this mammoth AI works? How does it digest this amount of data? Of course through interconnected, high-end devices powered by embedding “eyes”, named as Deep Learning. These artificial neural networks work on the principle of machine learning algorithms and simulate the complex structure of human brains. Employing mammoth data pools and lakes, deep learning determines and interprets intricate patterns, just the way humans do. In fact, some of the artificial neural networks are so adept at incorporating these patterns that they can even mimic the manner in which humans recognize faces.

DeepFace:  A Stiff Competitor of Human Brain

In terms of facial data, Facebook is the largest reservoir of facial data, and back in 2015, it came out with a cutting edge version of “tag photos” feature, DeepFace – it features a nine layer neural network that resembles characteristics in individual photographs with 97.25% accuracy. This fabulous technology not only connects your name with your face, but it can easily pick you out of a crowd, and the figure says a human brain is only 0.28% more effective than DeepFace.

Of late, Facebook has acquired a new patent, “Techniques for emotion detection and content delivery,” – it helps in capturing user’s facial expressions through the camera in real time while they scroll across their feed, recording their emotions for various content. This new-age technology can not only customize your Facebook feed, but can also link numerous live in-store cameras for a better shopping experience, piling up data from Facebook and determining the shopper’s present mood and preference.

Facebook and Beyond

Though Facebook is dominating the waters of facial recognition, there are several other companies that are trying their luck into this domain. Ebookers, a sub-site of Expedia has launched a tool named SenseSational, which employs real time facial recognition software to monitor users’ faces, while they peruse over images and sounds that appeal to the senses.

On the other hand, Singapore Technologies Electronics is using facial recognition technology to identify the faces of commuters, as they walk across fare gates and charges their prepaid account respectively. No longer the commuters have to show their fare card while standing in queue; thus it eases the crowd buildup during rush business hours.

In conclusion, companies can anytime look up to deep learning from any angle. The giant of artificial intelligence is forever hungry, you can feed it with data whenever you like, and see it expand and flourish.

Seeking an excellent data analyst training institute in Gurgaon? Look no further; DexLab Analytics is here. With a wide set of comprehensive Data Science Courses in Delhi, this institute is here to satisfy every data need.

Let’s Take Your Data Dreams to the Next Level

The original article first appeared on – https://www.entrepreneur.com/article/311228

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Reigning the Markets: 4 Most Influential Analytics Leaders of 2018

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Data analytics in India is grabbing attention. Data and analytics, together, they play a key role in delivering business opinions, which are high-yielding and relatively new. At the helm of such robust data analytics growth are leaders from numerous organizations who introspect into data to conjure up decisions as a seamlessly as possible. They are masterminds in the world of data analytics.

Reigning the Markets: 4 Most Influential Analytics Leaders of 2018

Here, we will talk about 4 most influential analytics leaders who acted as pioneers of bringing in newer technologies and life-changing innovations into the field of analytics, machine learning, artificial intelligence and big data across diverse domains.

Debashish Banerjee, Managing Director, Deloitte Analytics

With 17 years and more experience in predictive modeling, data analytics and data science, Mr. Banerjee’s extensive contribution in the fields of actuarial risk, data mining, advanced analytics and predictive modeling in particular is phenomenal. He started his career with GE, and initiated and headed insurance analytics, pricing and reserving team of GE, India – one of the firsts in India.

In 2005, he shifted to Deloitte with a mission to initiate the advanced analytics and modeling practice in India, through which he manages and offers leadership support to the Deloitte Consulting’s Data Science practices that stresses on AI, predictive modeling, big data and cognitive intelligence. He mostly worked in marketing, customer and HR domains.

Let’s Take Your Data Dreams to the Next Level

Kaushik Mitra, Chief Data Officer and Head of Big Data & Digital Analytics, AXA Business Services (ABS)

Experienced for over 25 years in integrating analytics, technology and marketing worldwide, Kaushik Mitra dons a lot many hats. Besides assuming leadership roles for diverse domains, like AI, analytics, data science, business intelligence and modeling, Mr. Mitra is at present involved in driving an array of data innovation coupled with technology restructuring in the enterprise, as well as coordinating GDPR implementation in ABS.

Before joining ABS, he worked with Fidelity Investments in Bangalore, where he played a pivotal role in establishing their data science practice. Armed with a doctorate in Marketing from the US, he is a notable figure in the world of analytics and marketing, along with being a frequent speaker in Indian industry networks, like NASSCOM and other business forums.

Ravi Vijayaraghavan, Vice President, Flipkart

Currently, Ravi Vijayaraghavan and his team are working on how to leverage analytics, data and science to improve decision-making capabilities and influence businesses across diverse areas within Flipkart. Before joining Flipkart, he used to work as Chief Data Scientist and Global Head of the Analytics and Data Sciences Organization at [24]7.ai. It was here that he created, developed, implemented and optimized machine learning and analytics driven solutions. Also, he held important leadership portfolios at Mu Sigma and Ford Motor Company.

Deep Thomas, Chief Data & Analytics Officer, Aditya Birla Group

“Delivering nothing but sustained and rising profitability figures through potent digital transformation and leveraging data, business analytics, multi-disciplinary talent pool and innovative processes” – has been the work mantra of Deep for more than two decades. Being the Chief Data & Analytics Officer for Aditya Birla Group, he spearheads top of the line analytics solutions and frames organization-wide initiatives and tech-induced programs to enhance business growth, efficiencies and productivity within an organization.

Initially, he headed Tata Insights and Quants, the much acclaimed Tata Group’s Big Data and Decision Science Company. Apart from this, he held a variety of leadership positions in MNCs like Citigroup, HSBC and American Express across US and India to boost global digital and business transformation.

This article has been sourced from – https://analyticsindiamag.com/10-most-influential-analytics-leaders-in-india-2018

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