Big Data

Netflix – Your New Big Data Leader

Netflix has changed the entertainment industry on its head in just about 4-5 years. We all know the transformation story of Netflix from a simple dvd mailing service company to a multi-billion dollar business enterprise. But, how it happened? May be it was Netflix’s unique idea of creating a modern video streaming website or its efforts to build a big data and analytics company that could predict customer insights well before others can. A big data company that excels in identifying, accessing and prioritizing customer’s entertainment needs. Netflix’s has currently 50 million subscribers around the world.

The company’s is always on the hunt for new technologies to improve its big data and analytics infrastructure. Netflix applies modern big data techniques to manage customer information. The company has it own big data federated orchestration system Genie to manage various big data jobs such as Hadoop, Pig, Hive and more. Strategically, the company attempts to use data virtualization techniques to garner new insights. The first step involves analysis and monitoring of customers’ data, done at a massive scale to predict their viewing habits. Netflix’ ability to come up with popular entertainment services can be linked to the company’s understanding of what its customers’ primarily want. Big data has put Netflix at a clear advantage and many other companies can also replicate its success by extracting value from big data.

Big data might be the driving force behind the recommendation engine of Netflix, helping in predicting viewing habits. But the sheer volume of data Netflix collects on a daily basis can make it challenging for any company to apply analytical skills which is key to establish a more customer-driven engagement. The real challenge in a data-driven environment is to provide a secure flow of information across business units. Dan Weeks engineering manager for Big Data Compute at Netflix explained that the biggest big data challenge at Netflix is scale. Globally, there are over 86 million subscribers of Netflix, streaming over 125 million hours of content per day. Dan said, “Netflix is a very data driven company. We like to make decisions based on evidence. We don’t want to make changes to the platform that we can’t substantiate will actually improve the experience for users.”

Netflix’s ultimate goal is to improve the viewing experience of its customers. For this reason, the company has some of the most sophisticated big data tools at its disposal that excel in generating more accurate and insightful analytic strategies.


Big Data is the New ‘Buzzword for Digital Marketers

The digital advertising industry is now being able to address some of its most fundamental challenges making use of big data technologies. Big data platforms bring the abilities to better connect seller with potential buyers. Understanding the need to revamp digital infrastructures for marketing services, companies have looked to combine new processes and delivery models. Simply put, the big data growth in the industry is just getting started. Digital advertisers are making every opportunity count by creating new forms of engagement with the modern customers. The world of online advertising has transformed in many ways due to the emergence of data driven marketing.

Big data is helping businesses to explore new ways of marketing, and giving them the potential to capture and analyze massive amounts of structured and unstructured data. This makes it possible for companies to discover new relationships, spot emerging trends and patterns, and carry out operations in a more efficient way. As a result, the long-standing impact of traditional advertising is slowly reducing in the industry. Now, it is big data that has become the backbone behind exchange of customer details, operations research and a range of other activities.

With big data, digital advertising firms can track the entire buying history and preferences of their customers and analyze data from both internal and external sources. Historic data offers key insights into industry trends and buying behaviors over time. However, companies fail to analyze data from sources such as photos and social media posts that are currently in the system. Big data techniques have been deemed successful in addressing the complexities as well as to facilitate inform marketing decisions and strategies.

The challenges to manage and analyze massively large data sets have been greatly reduced by big data analytics platform. Big data allows digital advertisers to focus on improving advertising platforms with more targeted and personalized ads, thus making adopt new approaches to customer engagement. The growing use of smartphones, has created a major opportunity for digital advertisers to take control of their online advertising business. The big data industry is seeing considerable investments from retail and e-commerce companies. Now, it is the time for digital marketers to make the best use of data for enhancing the shopping experience of customers.


A Guide to the Future of Analytics

The emergence of big data has been one of the main reasons behind the transformation of modern businesses. Big data has opened up new opportunities that would have seemed unimaginable only a few years ago. In these times, making the right investments in data and analytics can deliver the greatest business impact. Data as the main driver of digital transformation has gained much more strategic importance in an insight-driven business environment. IT companies have now finally started to take advantage of data’s full potential while looking to achieve the goals of a full-fledged data-driven organization. Against this backdrop, it seems today there is no lack of intelligent devices that are treating data analysis in a new light.

IBM has been a front-runner in the race to create smart systems, focusing primarily on predictive analytics and cognitive techniques. The technology leader recently unveiled a super-computer called which as the ability to ingest data at the rate of 67 million pages a second.

The purpose of this latest IBM innovation is to establish a question and answer dialogue between it and humans, whereby Watson will run unimaginable amounts of data and answer in plain speech and in real time.

Watson is a unique offering from IBM that aims to bridge the gap between humans and machines by applying Artificial Intelligence techniques. The next obvious question is how Watson would capture huge amounts of data and turn into an interface for human-machine communication. Perhaps, it should not be a surprise because analytics has made it possible to capture volumes of unstructured data from across the value chain.

Google has always been considered an innovator in this type of interaction. Google has long empowered data scientists to look beyond the complexities of traditional data management techniques. Moreover, Google technology initiatives have helped to build a greater understanding of data possibilities among IT organizations. The way NetSuite operates its cloud-based ERP system is another example which show how large volumes of data can be presented in a way that supports informed decision-making and human comprehension. 2017 could be the year of data analytics, and Data engineers can lead new approaches to data analysis by thinking more boldly about how to capture the missing human element in the field of analytics.