Tons of data is generated everyday in the industry. And making sense of this pile of data has become an important task for many businesses. To achieve this, they are turning into Big Data analytics and Data Science. Data Scientists have knowledge about various algorithms suitable for various types of data and these statistical algorithms are implemented in several programming language. Selection of the programming language depends on many factors. So here is the list of top 6 programming languages that are used by most of the data scientists and analysts.

1.  Python

2. R Programming

3. Matlab

4. Java

5. Julia

6. Scala

Read detailed review at https://www.technotification.com/2018/07/best-programming-languages-for-data-science.html

GST-Network (GSTN) is trying to provide hi-tech security and analytics center to give protect the data under the Goods and Services Tax (GST) for the cyber threats. GSTN will be appointing security companies by August to build up Security Management and Analytics Centre (SMAC). SMAC will implement data analytics to protect the GST system from cyber attacks and will provide a better and protected environment for GST ecosystem. Read more at: http://cio.economictimes.indiatimes.com/news/digital-security/paranoid-about-security-setting-up-analytics-centre-gstn-ceo/59092397

Very often a customer 360 view can be dangerous and distracting as it sets the organization of the track by providing it a false goal to pursue and diverts it from pursuing financially rewarding initiatives. As a consequence, business acquires a constant monitoring stage with their data and analytics investment. Customer 360 view data is not actionable until you don't apply analytics and you can't apply analytics until you know the business problem organization is wanting to address. A more active approach would require focus on identifying the decisions that an organization is trying to make about customers and validate, justify and prioritize those decisions. Read more at : http://www.datasciencecentral.com/profiles/blogs/the-danger-of-pursuing-customer-360-view

It has been evident that a great customer experience is one of the signs of a healthy business model. Machine Learning and Data Analytics are playing a fundamental role in building consumer intelligence systems. It is important to capture data and there is no single magic source to collect data. Telecoms are making billions by selling data. You need to ensure that the data is relevant to business. Once you have the right data, you are ready to model, design and engineer and deploy your 360-degree customer view platform and achieve the enhance customer experience for your organization.

You can read more at: http://www.datasciencecentral.com/m/blogpost?id=6448529%3ABlogPost%3A508502

While developing data strategies in the future, organizations must consider these new emerging trends: 1) Data's center of gravity is moving more to the cloud day by day, which means one should be looking to keep all their data tools for processing to analytics in the cloud. 2) Hybrid data technologies are critical to the cloud system and hybrid data systems like SQL Server, MySQL, etc. is predicted to become the norm by 2018. 3) With new tools for data analysis being innovated, businesses need to connect to many data sources that span across databases, Hadoop ecosystems, and web applications. Read more at: http://data-informed.com/how-to-capitalize-on-the-data-landscape-of-tomorrow/

In a dynamic business environment every organization is seeking profit maximization & risk mitigation approach, the article talks about the latter, in uncertain business environment business leaders at time of complex & critical decision making take decision on the basis of intuition (gut feeling) rather than holistic analysis of situation. Even with data backed decisions there is a narrower approach attached in form of point estimates & averages. In this article a new approach Prescriptive Analysis is used where business are simulating probabilities to reduce risk that helps in robust analysis. This approach gives us broader perspectives showing us a range of possibilities & helps in better decision making.Read Full article at :- Target=_blankhttp://www.forbes.com/sites/gartnergroup/2016/03/24/use-prescriptive-analytics-to-reduce-the-risk-of-decisions/#465f9994785b

If in 1 line I have to summarize the importance of article it will be, the solution is not limited to just analyzing a data, but also making sure it’s understandable & is communicated wisely to the end user for decision making. In the digital world huge amount of data is recorded every second, organization massive amount of time of monetary resources to analyse the data to churn out valuable information for decision making purpose, but unless & until these analysis are communicated in a right manner that could be understandable to the, otherwise its will be a sheer waste of valuable resources of organization. In this regard the article talks about “Info graphics” & the latest innovation in this field that can amalgamate business intelligence with narrative sciences.Read Full article :- http://www.forbes.com/sites/bernardmarr/2016/01/21/why-management-dashboards-and-analytics-will-never-be-the-same-again/#4cce3b7c3963

Big data analytics is becoming self-explanatory day by day to even a lame person who has lesser knowledge in statistics, analytics and data science. It is a positive sign with respect to current business purpose because we need real time analysis and that can be only possible if data interpretation and visualization becomes more feasible. There are different software like R, SAS and many other online service providers like google analytics, Piwik helps to create better data visualization and interpretation of customer and business data. Even our very own Microsoft excel has some in built data interpretation and visualization programs. But one program, called Quill, takes the trend a step further, producing text-based reports that explain the data clearly and concisely.  Think of it as an executive summary created by a computer to explain a set of data at the click of a button. So it’s time for personalize big data analytics.

to read, follow: http://www.forbes.com/sites/bernardmarr/2016/04/27/will-we-soon-no-longer-need-data-scientists/#540a99bf55f3

EMR (electronic Medical Record) adoption, big data and other trends are helping a lot in the generation of data in the healthcare industry. But data is not what drives the healthcare industry- managing this data does. In healthcare, data analytics is done in use cases. Multiple use cases are created according to the need like one while patient got admitted in some department, a use case gets created. To provide best services to patients timely, immediate access to patient’s data without the barrier of time or location. Read the full article here: http://www.computerworld.com/article/3038315/data-analytics/accelerate-time-to-value-with-healthcare-discovery-analytics.html

Technology is fundamentally transforming the world around us, in every aspect of our lives as well as in business. Budget 2016 has shown encouraging initiatives towards the commitment to focus on Digital India initiatives, technology platforms and data analytics to automation. The budget supports the few initiatives like-:

• Fiscal plans to fund the provision of entrepreneurship training across schools, colleges, and through an online program on a large scale

• An online procurement system for food grain procurement

• A new digital literacy mission scheme for rural India to cover 6 crore additional households in three years

To know more, please read the article by Jochelle Mendonca (Writer at ET tech)-:  http://tech.economictimes.indiatimes.com/news/internet/budget-2016-tech-announcements/51191308

Data analytics are the most essential part of any organization these days and requires efficient personnel having a greater skill set in data science. But, there is not enough parity between demand and supply. According to a recent study, it was found that there is demand for computer programmers with a background in data analytics, but out of the 332,000 computer programmers in America, only 4% had the necessary skill sets. So to bridge the gap, the online training method can be a helpful process and is flexible and this in turn enhances productivity. This is a continuous process of development and helps to figure out new talent within the organization. But all these processes can only be possible if colleges and universities encourage their student to learn data science and master in those skillet.

To read, follow:  :  http://www.cio.com/article/3033887/careers-staffing/can-online-training-bridge-the-big-data-skills-gap.html

Some volunteers of a nonprofit volunteer outfit are going door to door in Odisha. They are collecting data about schools, health facilities, Panchayat, roads, etc. These data points are being analyzed by a not-for-profit development organization which will use this data and will draft a development plan for Member of Parliament. The idea is to filter the data into meaningful information which will help in reducing the gap between real needs and actions. Some big consultancies are also working together with politicians for the same purpose. Data analytics tools are used to determine demographic profiles and socioeconomic aims. Read the full article here: http://articles.economictimes.indiatimes.com/2016-02-02/news/70283182_1_data-analytics-tools-prime-minister-narendra-modi

Modern customer relationship management (CRM) solutions are fast, sharp, and are driven by cross-platform big data. These changes represent a move towards an economy driven by the Internet of Things (IoT). In this article, the author analyzes the predictions of recognized CRM experts about the future of CRM. They are -  Wearable Technology, Wearable Tech for IoT Insights, Bigger Data Analytics, Mobile Data Collection, Increased Predictive Analytics. Read more at:  http://it.toolbox.com/blogs/insidecrm/whats-in-store-for-crm-wearable-technology-bigger-analytics-and-more-70292

Data analytics can extract patterns, trends, and information from large sets of data. We often use the term “business intelligence,” for data analytics. But, it’s useful to distinguish the terms. Business intelligence uses data to improve management and operations. Data analytics improve that data before acting on it; further, you can slice the data to extract insights that in turn provides a competitive advantage to your organization. Data analytics can put any company ahead of disruptions, leveraging the data to augment your competitive position relative to others in your field. Read more at: http://www.business2community.com/business-intelligence/company-needs-data-analytics-01359169#pd3tMLVLOM7fcY29.97

In business, one not only has to keep a track on competitors and a close watch on the market but also keep a tab on what the customers are feeling, and how they are responding about their products in social media. Luckily with the advancement of data analytics many such tools are available and are becoming popular. One such marketing tool is a search engine which searches any social mention of the topic in social media. These platforms enable a business leader to evaluate customer sentiments and use it for business development. Read more at:  http://www.huffingtonpost.com/jayson-demers/7-marketing-tools-to-find_b_7605262.html?ir=India&adsSiteOverride=in

Evidences showed that recruitment have not been so easy during past years. Recruiting new employee requires a huge investment for most companies, specifically in managerial or professional role, which absorbs large proportion of company’s revenues. In the presence of big data, planning and strategies can improve recruitment process. US financial services company used big data analytics to examine the performance of employees. What they observed was that top performers were mostly those who had higher education. Office equipment manufacturer Xerox used analytics to study the performance and profile of candidates recruiting for its call centers which reduced the staff turnover of 20%. Big data is attracting employees and with the help of some tools such as Cornerstone and TalentBin (tools to crunch data) made it easier to find candidate for the right position. Online recruitment services are also enjoying the benefits of big data. Say for example it made easier to look at what are the areas of interest, average spending, experience, location of service. So, it is easier to plan ahead and prioritize. Read more at:

http://www.smartdatacollective.com/bernardmarr/327498/how-big-data-changing-recruitment-forever

Industries are flooded with data and this data can be used to extract a lot of money if only we knew how to use it. With the rapid advancement of technology, we have high-speed networks and improved algorithms for analytics. Various industries including healthcare and financial services are basically resting on terabytes of valuable data and information. Six best methods for monetizing data are as follows:

1. Building up trust and neutrality among the customers.
2. Anonymization and aggregation of data is required.
3. To acquire permission of utilizing the data that is not owned by the company.
4. To consider spinning out the data monetization unit.
5. Provision of data analytics in real time.
6. Furnishing customers with self-service capabilities.

In order to know more about data monetization, please follow the link: http://www.cio.com/article/2941291/big-data/memo-to-cios-cash-in-on-that-data.html

Just like other areas of economy, marketing, too, has been impacted significantly by the growth of data analytics. Although the importance of analytics has been recognized in marketing, yet it is observed that in most cases the tools are not being used efficiently. For this, aligning data with the goals of the company needs to be done. Secondly, the smooth transition from big data to useful data and determination of the relevant metrics and adoption of those metrics are required. And last but not the least, hiring of the right people with analytical and creative minds to properly use the data is imperative. Read more: http://www.forbes.com/sites/johnrampton/2015/06/21/how-can-cmos-make-sense-of-big-data/

Planning before working out is the most basic idea. A planner successfully merges both aesthetics and practical planning. But a strong design comes from the collected data. Combining user and sales data, Ford F-150 has been designed to reduce weight and increase sustainability which are made keeping in mind both environmental and business sense. Though A/B testing was a popular method of creating effective marketing choices due to its manufacturing constraints, companies nowadays use data gathered by observing public interest to create new products or make changes to earlier products. With increasingly complex algorithms, architectural design is now getting more accurate. With faster computing power, various tests can be done to establish strength and quality. Read more about this article by Chris Towers (Big Data Divisional Head) at:  https://channels.theinnovationenterprise.com/articles/designed-by-data

The film Moneyball based on a 2003 book, talks about the Oakland Athletics baseball team whose focus is on the team's analytical, evidence-based approach to improve the baseball team despite its poor revenue system. This film made the plot for professional sport associations to spend big on analytics. Analyzing data points captured by video cameras around the stadium uncover patterns that coaches and players might miss. Data can also be collected by wearable devices to help prevent injury by measuring its likelihood. So, companies need to follow get up and move up to the major leagues of Big Data. But predictive analytics can decrease efficiency as supporting analytics platform records, analyzes and visualizes trends. Read more about this article at: http://www.tibco.com/blog/2015/05/26/how-big-data-analytics-are-transforming-sports/