After being cautious of big data for several years, the marketing and advertising technology sector is adopting it cautiously nowadays. Big data analytics has emerged to be a handy tool for these sectors as it allows a more sophisticated analysis of things to get deeper insights into a consumer's behaviour pattern.  The data is gathered using consumer’s digital footprints like googling and facebook liking etc. Then, this information is used by companies to identify the behaviour of the existing online users to offer them the best targeted deals and services which are specially tailored for them. Therefore, this allows the marketing and advertising sector to create more focused, targeted and, effective campaigns by saving money, targeting the right consumers for the right products and increasing the rate of conversion of the deals offered. Read more at:https://www.entrepreneur.com/article/293678

The emergence of massive unstructured data sources like Facebook and Twitter has created a need to develop distributed processing systems for Big Data Analytics. Hadoop (A Java based programming framework) has become the first choice of developers and industry experts mainly because its: Highly scalable, flexible, and cheap. An application is broken down into various small parts which runs on thousands of nodes to achieve fast computing speed and reduce overall operation time. Hadoop architecture continues to operate even if a node fails. Its incredible design allows you to process large volumes of data and extract computationally difficult features of users/customers.

Read more at : http://www.datasciencecentral.com/forum/topics/how-to-use-hadoop-for-data-science

According to Nasscom (National Association of Software and Services Companies) the expected rise in the Indian business analytics sector is 8-fold (from $2 billion to about $16 billion). It targets to make India among the top three big data analytics market in the world. To achieve this target Nasscom is partnering with its members to build a multi prolonged approach that encompasses skill development, thought leadership, products and platforms. India is an emerging hub for analytics solutions across the globe. The witnessed rapid growth is due to increased demand for cloud based and predictive analysis solutions by industries like BFSI, retail, telecom and healthcare. Even the requirement of manpower in this sector would increase magnificently in the next 5 years.

It is the rapid advancement of artificial intelligence and deep learning algorithms which enabled the development of machines which can do tasks that requires deep expertise and skills. Read more at: http://economictimes.indiatimes.com/tech/ites/big-data-analytics-to-reach-16-billion-industry-by-2025-nasscom/articleshow/52885509.cms

With regards to big data analytics in the healthcare industry, there's a noteworthy contrast between beginning an activity and succeeding with it.  We have to collect data systematically. Organizations should also conduct regular reviews of their data integrity and health information management programs to help clinicians to collect important data in a standardized, and accurate manner. Big data analytics is costly and hiring an outsider with more experience might be interesting for suppliers who are feeling lost. Outsourcing can also be risky when it comes to data security. Read more at: http://healthitanalytics.com/news/how-to-build-a-successful-big-data-analytics-program-in-healthcare

The term big data are applied to data sets which is beyond the ability of traditional databases to capture, manage, and process the data with low-latency. Big data analytics can be real-time processing or streaming analytics. The primary goal is to help businesses to use data to be well informed about their customers, decisions they should be making, improving efficiency and various other use cases. For more read: http://www.cbronline.com/news/big-data/analytics/big-data-analytics-what-it-is-and-why-you-should-care-4894627

Business houses are now acknowledging big data. Many organizations are realizing how much Big Data affects employee learning. Additionally, Big Data can help organizations in order to gain higher efficiency, maintenance and engagement. The ways in which organization's learning programs can benefit from big data analytics are: Hyper-personalize learning to enhance business performance, higher return on Investment (ROI), Visualization i.e. Better learning, i.e. Big Data is equal to better business opportunities. Read more at: http://tech.firstpost.com/biztech/why-big-data-analytics-is-a-big-boon-for-organisational-learning-312790.html

Big data have existed since the time of the cave man existed in physical paper and other analog forms (stone, papyrus, tape) and was largely inaccessible. With the inception of commercial Internet & new forms of commerce and social media, we can access information of "open source". Now technology can connect streaming and near real-time data to generate information very fast. Dynamic machine-learning algorithms can also help to discover hidden patterns and associations and graph databases has the ability to query and explore entities and their relationships in order to understand how opponent operates. It was also found that tools for geospatial analysis can help analysts to understand how events and groupings are related in space and time. To know more, please read the article by Mark Testoni (Writer at Homeland security today.us) -: http://www.hstoday.us/columns/critical-issues-in-national-cybersecurity/blog/big-data-analytics-from-forensics-to-foresight/d0c045fe32568eedefda4195d46472e6.html

In the years, succeeding the financial crisis, the banking sector was restructured ranging from changes in regulations to customer service. The major problems that banks are facing include customer dissatisfaction, fraud, increased competition and regulations and all these issues can be solved using Big Data analytics. By leveraging transactional, behavioral and social data, banks can provide a hyper-personalized customer service. Risk management is another area where analytics can be of help. Big Data analytics can detect cybercrimes and predict the location of attack. It can also identify deviation in customer behavior which is indicative of fraud. Big Data technologies can be used to integrate external watch list screening system and unstructured emerging data sources. There is a huge scope for newcomers in Fintech sector to exploit Big Data as they are built keeping analytics in mind. The big banks should adopt new technologies to leverage the wealth of data they possess and maintain a competitive edge. Read more at:https://channels.theinnovationenterprise.com/articles/analytics-in-banking