Today world has become smaller and faster, with increasing computation speed decisions are done in seconds instead of days. Product information and comparison is available on any device any time. Real Time analytics involve solving problems quickly as they happen or even before they happen. Companies now have more insights into their assets. Several industries are using streaming data and putting real time analytics. The big data revolution has further accelerated the demand of real time analytics to analyze customer behavior. Gone are the days when decisions were based on data stored on a disk , actions are taken on streaming data. Read more at: http://www.datasciencecentral.com/profiles/blogs/do-you-know-what-is-powerful-real-time-analytics

Supply chain management is a field where Big Data and analytics have many applications. Organizations apply big data analytics in supply chain management. Supply chains have been driven by statistics and quantifiable performance indicators. But the sort of analytics, which are really revolutionizing industry today are real time analytics. Traditional data monitoring involves sales and order tracking and point of sales data. It is now being supplemented with weather, events and news, with the aim being to create insights in the short term. For more read the article written by Bernard Marr (contributor) : http://www.forbes.com/sites/bernardmarr/2016/04/22/how-big-data-and-analytics-are-transforming-supply-chain-management/#5c0319b44c2d

Analytics help retailers move to a unified commerce experience and allow for more targeted, cost-effective marketing. Advanced analytics is used for the optimization of merchandise planning. Real-time analytics is integrated with customer and product information across all channels. Retailers have the ability to use science and algorithms to optimize pricing strategies to reduce markdowns, improve demand forecasting to optimize inventory, localize assortments and optimize space planning. Advances in software and the occurrence of cloud-based solutions enable retailers to think about accelerating their upgrade/replacement cycles. It will help limit overstocking and discounting. With real-time analytics, retailers can market to consumers on a 1:1 basis based on customer context. Retailers have the ability to know what customers have in their closet, purchase behavior and preferences. For more, read the article written by Forrest Cardamenis : 

http://www.luxurydaily.com/analytics-offer-solutions-to-merchandising-and-marketing-problems-brp/

Clickstream is recording of the parts of the screen of a computer user clicks on while web browsing or using another software application. Clickstream Analysis refers to collecting, analyzing, and reporting the data about visitors visit. This is generated by recording the succession of clicks each visitor makes. This helps you to get insights of the behaviour of the visitors. Hence, you can manouver your strategies as per this analysis. It gives you the information of how long a visitor stayed on your website and how often he returns.  This gives a wealth of information to be analyzed.  To know more about clickstream data analysis go through the article written by Jaoa  Correia at: http://www.blastam.com/blog/index.php/2015/04/move-into-limitless-world-of-clickstream-data-analysis

According to a research, use of Customer Relationship Management (CRM) tools have increased to $23.2 billion market share in 2014. Now, more companies are venturing into CRM solutions designed for mobile environment. It has been seen that sales team has improved their productivity by 15% more by using CRM tools in mobile environment. Some key features should be kept in mind while choosing mobile CRM. They are: Enterprise Level Security, Device Compatibility, Distilled Feature Sets, Data Aggregation, and Real-Time Analytics. Read more at: http://it.toolbox.com/blogs/insidecrm/5-key-features-for-your-mobile-crm-68505

Large amounts of real-time data is being daily generated by internet usage. Nowadays, devices are being interconnected and smart products are also connected with the internet. In order to use this data efficiently, organizations need to re-structure their supply-chain. The motivation is not just to use historical data in the traditional manner; but to combine data from multiple product interactions generated by both consumers and suppliers, connected via cloud portals. Supervised machine learning can search for and capitalize on the patterns and relations that they derive in the data and help in supply chain based decisions. Once implemented, they can be continuously evaluated and improved based on performance. The end aim is to accurately predict the attributes of future demand. Read more at: https://hbr.org/2015/06/inventory-management-in-the-age-of-big-data

We know how big data has helped organizations achieve big success in almost every field. Today, when everyone is in a race to establish a competitive edge over the other, businesses want their data and analytics to be real time or near real time so that they can act quickly. Mary Shacklett, president of Transworld Data, elaborates for us four ways real time analytics lead to competitive advantages. They are:

• Buying Preferences

• Network Intrusion detection and forensics

• Logistics Orchestrations

• Predictive maintenance

To know what these systems had in common follow the link http://www.techrepublic.com/article/4-ways-real-time-analytics-lead-to-competitive-advantages/

Big data combines unstructured data with structured data to produce a report which provides a complete view of the organization. This report helps in decision making. Big data provide real time or near real time data. According to Mark Shacklett (President of Transworld Data), big data analytics results have impacted corporate revenues, expenditure and customer satisfaction. Web-based analytics on e-tail users helps in generating more sales by assessing customer preferences. Network diagnostics toolset analyze network and machine-generated data and produce predictive reports. This tool set gives a real-time view of network traffic. Sensors placed on railways and tram tracks, help crew members to proactively repair or replace equipment and railway tracks before they fail. Read more at: http://www.techrepublic.com/article/4-ways-real-time-analytics-lead-to-competitive-advantages/

According to Mary Shacklett (president of Transworld Data), organizations need big data and analytics capabilities for immediately transferring big data into actionable decisions. According to a Gartner September 2014 report, there is an increase in investment in big data by 64% from 2013. Jeff Kelley (Big data analytics analyst from Wikibon), says that “customers expect personalization when they visit websites, so companies need to develop analytical capabilities and in the long term apply real-time will grow as Internet of Things.” Preventive maintenance analytics can be developed, if data on the Internet to thing can be analyzed. To know more about real time analytics and Internet of Things read on:  http://www.techrepublic.com/article/surge-in-real-time-big-data-and-iot-analytics-is-changing-corporate-thinking/

Analytics is seen as a ladder to succeed in today’s world. It reminds everyone of the benefits that one can achieve with its application in business. But is analytics always useful? What people chose to ignore is its downside. In retail sector, although analytics helps to predict demand, but it also helps to predict the employees required to meet the demand. This in turn, leads to less stable work hours for part time workforce. To reduce the harm to real people, retail analytics should be used in a responsible manner.

To know more, read the following Forbes article:

http://www.forbes.com/sites/sap/2015/04/15/abusing-the-power-of-retail-analytics/

Data Analytics is used in an ample number of ways to achieve a competitive advantage over other businesses. The various areas are - Big Data and Information Optimization helps in determining an organisation on how they can apply the present analytical access patterns and skill sets though it is still critical to audit the interaction between the analytical assets and core database system. Visual Analytics and Data Discovery gives guidance in finding a trend in the data set by developing various hypotheses and visualizing the complexity of the diverse data set. Companies need to inspect on different patterns and accord in the data for future benefit using Predictive Analytics. Right Time and Real Time Analytics are used to grasp on how customers are handling data analytics for managing industry. 

For more Information follow 

http://tonycosentino.ventanaresearch.com/2013/03/11/the-four-pillars-of-big-data-analytics/