Category Archive: Big data training

Flipkart Launches a New Internal Wing AIforIndia to Bet Big on Artificial Intelligence

Flipkart is strengthening its base in the field of Artificial Intelligence, and so far, this year has been treating them well. After pegging fresh influx of funds, appointing a new CEO at the helm of affairs and reportedly thwarting its tailing rival, Amazon in September, Flipkart is all set to enter the most promising arena of artificial intelligence and machine learning, NOW.

 

Flipkart Launches a New Internal Wing AIforIndia to Bet Big on Artificial Intelligence

 

In an interview to a leading daily journal, Sachin Bansal, the notable co-founder and Chairman of Flipkart is found saying – “we ready to invest hundreds of millions of dollars” in the AI gambit over the next few years. “This is the next big thing for us, where we are betting big on the use of AI and machine learning to solve problems at Flipkart. India’s problems are unique and we need to apply AI in the ecosystem to solve Indian problems. We believe that some of the focus areas for AI in developed countries cannot be applied for India. At Flipkart, we will solve problems differently because the underlying problems (in India) are different,” he states, adding that they has already started building the needed infrastructure, recruiting a dozen AI buffs and establishing partnerships with crème de la crème educational institutions, including the IITs to give a robust push to its inspiring AI initiative.

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Top 6 Big Data Trends for 2018

Big data is expanding, and by next year almost a majority of businesses will be attracted towards the brighter prospect of this cutting edge technology. Even this year saw an enormous increase in volume, variety, velocity of data, which assures that the next year will witness more data, more numbers.

 
Top 6 Big Data Trends for 2018
 

Data science pundits have predicted some of the leading trends that would be in the forefront in the big data revolution 2018. Come, let’s take a look:

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The Impact of Big Data on Marketing

The Impact of Big Data on Marketing

 

In marketing, the analysis of data is a highly established one but the marketers nowadays have a massive amount of public and proprietary data about the preferences, usage, and behavior of a customer. The term ‘big data’ points out to this data explosion and the capability to use the data insights to make informed decisions. Understanding the potential of big data presents various technical challenges but it also needs executive talent devoted to applying the solutions of big data. Today, the marketers are widely embracing big data and are confident in their use of analytics tools and techniques. Let us learn about the ways in which Big data and analytics can improve the marketing efforts of various businesses around the around.

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For Long-term Digital Transformation Plan, Big Data is the Key

Big data and business analytics are like two sides of the same coin. Here, though the coin represents digital transformation – but reports from consulting and services firm HCL Technologies are pointing that many companies are not being able to harness these new-age technologies to their fullest capacities resulting in a loss of digital transformation efforts.

 
For Long-term Digital Transformation Plan, Big Data is the Key
 

When asked Anand Birje, the corporate vice president and head of HCL’s digital and analytics domain, he has this to say, “Over the past four or five years, enterprises were pushed hard to do anything in the field of analytics, big data and digital transformation. They were being pushed because there was this fear about what their competitors might be doing, so there was this feeling that they had to do something digital.”

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Here’s ALL About Global Hadoop Market and Investment Report 2017

According to a market research report, Global Hadoop market – industry analysis, share, size, growth, trends and forecast, which was once estimated at a value worth USD 1.5 billion in 2012, is now expected to hit $13.95 Billion mark this year, 2017 with a CAGR of 54.9%.

 
Here’s ALL About Global Hadoop Market and Investment Report 2017
 

The advent of Hadoop platform stemmed out from the growing urge to manage problems that resulted owing to a lot of data – mostly a concoction of structured and unstructured data – that failed to fit properly in the traditional data storage and management systems, like tables. The play of analytics got intense, more complicated – both computationally and logically – hence the need for Hadoop is more than ever. This is similar to what Google was doing while it was on an endeavor to examine its user behaviors and index web pages, with a view to enhance its own performance algorithms.

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How to Secure Big data While Harnessing Its Big Power

The term Big Data stands for data that is humongous. Large volumes of data are being churned out every day to meet business needs.

 
How to Secure Big data While Harnessing Its Big Power
 

Business analytics is the bedrock of an organization. It uses data for proper analysis of business objectives, later on which helps in making better decisions and future profit generation. Also, it aids in determining the actual reasons of failures, re-evaluating risk portfolios, and detecting undergoing fraudulent activities before they swell up to affect business operations.

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Streaming Huge Amount of Data with the Best-Ever Algorithm

Can you measure water coming out of a fire hose, while it’s hitting your face? No? Then how would you calculate the amount of data that is constantly being churning out of numerous social media platforms? In simple terms, it’s not feasible, unless you opt for streaming algorithms – these are computer programs that execute such on-the-go calculations.

 
Streaming Huge Amount of Data with the Best-Ever Algorithm
 

Data flow is constant and humongous – in order to strategically record the essence, the rest of the data is mostly forgotten. A large pool of data scientists is constantly looking for ways to build a better, improved streaming algorithm, but now I guess their search has come to an end, they have invented something incredible to vouch for. This new, best-of-the-lot streaming algorithm performs miraculously by grasping just what it seems to be necessary, ignoring others. It remembers just that which it has seen the most, and that gives it an upper hand.

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Is Change the Only Constant: How Analytics has Changed, while Staying the Same Over the Last Decade

Data analytics is evolving. Coupled with Big Data, it is changing the topography of almost everything.

 

Is Change the Only Constant: How Analytics has Changed, while Staying the Same Over the Last Decade

 

Each year, more and more companies are allocating their time and budget to exploit and understand vast pools of data strewn across them, both inside and outside company files. Of course, Big Data and Analytics is selling like a hot cake today, but what is its story of evolution? How the technology flourished 10 years back?

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Revising the Basics of Big Data Hadoop

Big data is a very powerful term nowadays. It seems to be a large amount of data. Big data means large amount of structured, unstructured, semi-structured data. We get data continuously from various data sources.

 
Revising the Basics of Big Data Hadoop
 

Just have a look on how we get data.

 

Nowadays we are living in a techno era in which we need to use technology so that’s why we are generating data. If you are doing any type of activity like – driving car, having some shakes in CCD, surfing internet, playing games, emails, social media, electronic media, everything plays a crucial role to develop big data. 

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Time to Change the Game of Online Lending With AI and Big Data

As digitization grows in size and width, more and more companies are seeking ways to modify their digital lending services. It would be effective as well as profitable for both borrowers and lenders. And as a topping on the cake, companies resort to Artificial Intelligence and Big Data as they believe they are the future powerhouse of loans.

 

Time to Change the Game of Online Lending With AI and Big Data

 

Originally banks being the lenders make the lending decision based on a loan applicant’s credit score – which is a 3-digit number collected from renowned credit bureaus, like Equifax and Experian. Credit scores are obtained from large piles of data, such as credit history length, payment history and credit line amounts, and are used to decide whether the applicants would be able to repay their debts. They are also good to determine the interest rate of loans.

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