Dashboards offer a unique and powerful solution to an organization's need for information. Nowadays it has become a very powerful tool to gather inner facts for decision making.  One can find various ways to create effective dashboards from a visualization and interactive perspective, but there is a need to understand the psychological aspect also. By taking into consideration the various psychological factors, we can develop more effective and informative dashboards. The three most important psychological factors are:

1) The curious nature of humans.

2) An eye for style.

3) The need for autonomy.

 To take a closer look at each point, Please follow this link: http://www.dundas.com/discover/article/the-psychology-of-dashboards/

Now Analytics can also predict weather for as long as 40 days before.

EarthRisk Technologies has come up with an analytical model that can predict extreme weather events. This model is designed in such a way that it can identify different patterns of weather which involves intensive calculations. With the help of historically available data, it compares with the present conditions and uses predictive analytics to forecast the weather 40 days in advance.

Knowing advance weather forecasts will certainly help industries in the utility, energy and agricultural sectors as they heavily depend on weather information. With the help of this model, proper timely decisions can be taken.

To gain more insights on how Analytics are helping in predicting weather you can go to http://venturebeat.com/2013/05/10/big-data-can-predict-weather-up-to-40-days-into-the-future/ .

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/

Well, nowadays retail banks are more focused in implementing data analytics techniques and models into their day to day decision making processes. Data analytics not only provide solutions to attract and retain profitable customers but also by the help of various tools and techniques like data discovery and visualization, it is possible to analyze the various aspects which are associated with customers. Retail bankers are trying to discover the relationships and correlations in large amounts of data using customer intelligence derived from analytics. Big data analytic enable them to track customer behavior and preferences to achieve higher level of customer satisfaction which definitely helps to achieve stakeholder’s wealth maximization. For more information, please go through the link: http://spotfire.tibco.com/blog/?p=22990

‘Big data’ is a combination of four ‘V’s: Volume, Velocity, Variety and Value, in structured/unstructured way. The data should be organised in a proper architectural form and then different analytical tools can be applied. The common analytical tools like agent-based modelling, neural networks, factor analysis, cluster analysis, time series analysis can be used to do proper analysis of the ‘big data’.

For more information, please go through: http://www.scientificcomputing.com/blogs/2014/02/big-data-analytics-continues-evolve

While solving problems on Analytics, many times it happens that the given datasets are really complex to analyze as they overlap each other. With Interactive Visual Analysis (IVA), the task becomes easier, where the datasets can display the level of interactions between them without overlapping each other.

By developing the IVA, one can gain knowledge about the datasets, which is not apparently noticeable. Not only this, IVA involves formulation and testing of hypotheses and one can also explore the correlations between the different variables.

 Sounds interesting? Watch the video here: https://www.youtube.com/watch?v=UcYRrPqC5A8

Movies! This word creates a taste of entertainment, a sense of refreshment among the minds of audience. We all would like to see movies that satisfy our genre-wise thirst. Also we prefer watching movies that includes our favorite stars or from our favorite directors or even sometimes we prefer watching movies from our favorite production houses.  don't we? Even, the ratings given by movie rating agencies and critics affects our decision about whether to watch a movie or not.

Now a days, our advantage is that we can predict how a movie will perform by using various analytics models.

Read more at

http://www.kdnuggets.com/2013/12/movie-analytics-india-dhoom-3-to-don-3.html

To find the best tools and techniques for appropriate human resource selection must be the prime focus of a HR manager. The enhancement of the recruitment process can be attributed not only to the social media techniques but also to the data analysis, redefining recruitment. Data analysis helps in making accurate decisions faster which ultimately leads to a proactive business. The employee turnover can be reduced by analysis of the proper reason using sentiment analysis. Predictive analysis helps in eliminating the guesswork factor.

For more information please go to

http://theundercoverrecruiter.com/big-data-recruiters/

Analytics Platforms are offering greater insights into real time surveillance of disease outbreaks. This will be helpful for countries like India, where population density is high. Due to the population size and density, India is prone to infectious diseases and controlling the outbreak of the diseases is becoming difficult.

With the help of predictive modelling, the Analytics Platforms can be used in determining the severity and spread of the disease. Based on these, the control measures can be applied accordingly.

For more information, please go through the link http://articles.economictimes.indiatimes.com/2014-01-31/news/46870122_1_disease-outbreaks-notification-system-syndromic-surveillance

The last five years, we have seen a massive upsurge of data; we have generated 90 percent of the entire world's data in the last two years!!! Why today analytics is so successful? Just because of availability of data? No! We have to admit the technological advancement we made through the last decade to analyze the available data, also the success can be attributed to the decreased cost of storage space. Twenty years ago, we had all the data analysis tools in place but data was scarce. Today there is a frightening abundance of data... But then what to do with this available data and how! Yeah we got the techniques, but we need the applicability mapping... Think about the applicability of analytics into the telecom sector, which represents an agile supply chain management ...These examples points to the tremendous possibilities that big data offer in telecom sector. But we must never forget the underlying secret: only blue-blooded telecom experts can usher in this exciting telecom future. Today's big buzzword is big data. Its companion, buzzword analytics, is also a big favorite. There are good reasons why this is so. 

For More Information Go To This Link:

http://www.business-standard.com/article/management/a-secret-about-analytics-114030200628_1.html

Traffic congestion is a major issue in major cities of the world. While there are discussions going on how to optimize this problem, Analytics can be seen as a major problem solver. With the help of Analytics, traffic systems will become 'smart'. They will predict the flow of vehicles in future and depending on that information, decisions can be taken in managing congestion.

In fact, the City of Cologne, Germany has implemented Analytics to make traffic systems smart.

To see how they have done, please go through this link: http://www.futuregov.asia/articles/2013/jan/22/german-city-uses-analytics-solve-traffic-jams/. 

 Ever heard of Location Analytics?

Well, that is what the next level of analytics is. 

Willing to learn the consumer behaviour deeply, the companies are investing in technologies that can track the locations of their customers, and also gain insight into what they are buying and where they are buying. Location Analytics can help the companies to fine tune their inventories, effective pricing of their products and much more. They combine all the data - ranging from customers' purchasing information to Geographical Information System data in order to study patterns and gain understanding of how, where and why customers buy. 

Go over to http://www.allanalytics.com/author.asp?section_id=1411&doc_id=257137 to have an in depth knowledge of Location Analytics and to http://www.bigdata-startups.com/BigData-startup/world-largest-coffee-shop-starbucks-grinds-lot-data/ to know how the world's largest coffee shop Starbucks is implementing Location Analytics.

The numbers are coming in thick and fast but can big data and advanced analytics influence a team’s performance in the Soccer Premier Leagues?

Since the 1950s, when retired RAF pilot Charles Reep’s roughly-researched analytics led to the long-ball strategy, the football community has been enthralled by statistics. Today Premier League teams and their followers are being inundated with data as high-tech cameras capture every pass, dribble, free kick or touch of the ball while monitoring players’ xy coordinates every tenth of a second throughout the 90-minute match! What we call it as?

For more information check the following link:

http://knowledge.insead.edu/operations-management/beyond-moneyball-data-mining-the-premier-league-3155

Big Data and Analytics have become very much popular nowadays. Every industry is incorporating analytical techniques to handle big data and predict future outcomes. The recent addition in the industry list to play with data is the airlines industry, who have started to love it. From carrying on regular and vital maintenance activities & optimizing them, to capturing customer behaviour in purchasing airline tickets, Big Data is surely helping the $743 billion global airline industry to earn profits. In what ways Big Data is actually supporting the airlines industry?

Have a look at http://www.datanami.com/datanami/2014-01-03/how_big_data_helps_airline_profitability.html for more information.

Predictive analytics is the next generation of analytics which is important for the engineering and construction industry. Data makes up the building blocks for analytics. But instead of using data analytics to make sense of the past — to understand what we have done and what trends we can pick out from our past behaviour — predictive analytics uses data to predict what is likely to happen. When you use predictive analytics, you let the data tell you the answers that you may not be aware of; that are not obvious to you.  You’re looking at data you may not be collecting yourself. Target is pouring over data and finding the themes, patterns and relationships to build predictive models to achieve business outcomes.

The traditional ways of handling data do not afford easy ways to handle large number of data(in terabytes) which can nowadays be easily solved by cloud computing.

The main advantages of cloud computing are:

1)      removal of the concept of limited storage infrastructure

2)      elimination of the need of building IT infrastructures to deal with obstacles

3)      reduction of the cost of infrastructures and charges only for the resources actually used

The main challenges for cloud computing are:

1)      shipping of hard disk drives to cloud providers

2)      data transferring through web

According to Gartner's Hype cycle, cloud computing has reached a maturity that leads it into a productive phase. This means most of the main issues with cloud computing have been resolved.

In recent years, data mining has been used widely in the areas of science and engineering, such as bioinformatics, genetics, medicine, and electrical power engineering. Several researchers and organizations have conducted reviews of data mining tools and surveys of data miners. These identify some of the strengths and weaknesses of the software packages. They also provide an overview of the behaviors, preferences and views of data miners. How about reaching a few inches deep into the applicability and usability of data mining which is the analysis stage of a typical KDD in terms of Education?

Please Follow this link

http://www.thehindu.com/news/cities/chennai/harnessing-data-mining-to-revolutionise-education/article5690365.ece

With the release of its first ever Advanced Analytics Magic Content, the information research and technology advisory firm Gartner reveals Rapidminer is fast emerging as a leader in advanced analytics as against the legacy Business Intelligence Softwares like SAS. 

Big Data and Analytics was one ofthe most hot talks over the internet in 2013 and it is likely to trending upwards in 2014 also as companies are making use of predictive and advanced analytics more and more as business environment is increasingly becoming volatile. 

Seeking customer feedback is an important part of any company or organization to ensure that their products remain in line with what the customer wants. Its nothing but adhering to 'Customer Is King' principle. As business world is becoming bigger and bigger, companies are coming out with more and more new products, it is very important to hear the 'voice of the customers (VoC)' to stay ahead of the competition. Not only this, by gathering customer feedback, companies can bring in new innovations in their products.