Nowadays, daily sales are not enough to ensure longevity of a business. Markets are beginning to realize the necessity of predicting future sales. They are tapping into the business trends and applying machine learning algorithms on big data to allow businesses to maximize their efforts in the most profitable areas. By knowing ahead of time, what a customer will buy, profits can be maximized and businesses can be tailored accordingly. Predictive Analytics allows us to segment customers, find patterns in their behavior and take preemptive measures to reduce churn. Analytics can be used to identify correlations and also to find causation. It can allow us to predict an individual's purchase behavior once we understand the causation underlying a pattern. Read more at: http://www.computerworld.com/article/2934086/business-intelligence/marketers-are-betting-big-on-predictive-analytics.html

Big data, legacy data, operational data and streaming data - these are all impacting the ever-increasing volumes, velocity and variety of data. - Deepak Belur (In4Group). Data and analytics have become essential to formulate critical business decisions. The big data storage technology is capable of analyzing massive amounts of data. But, analyzing a big data rarely gives you a full picture. To analyze full picture, a company need to analyze “unstructured data” which is present in mainframe servers. This data can be analyzed by using performance analytics. Enterprises need to combine relational and non-relational data, open system and mainframe, to retrieve the combined information via a simple, single query or request. And they need agile data architecture. Timeliness, accuracy, usability and accessibility of data are critical factors in the successful decision making process. Read more at: http://www.itweb.co.za/index.php?option=com_content&view=article&id=143791

Even in this multichannel world, customers still prefer to call in and hence voice channel is critical to a business. These days’ businesses are coming to a standstill when it comes to listening to conversations that flow through their voice channel as they are stuck on sampling and high cost manual monitoring. A recent survey showed that it is important to link online marketing to offline sales.
Mining for the truths and hidden meanings from these conversations is crucial. Previously automatic data mining of the voice channel was unattainable. But now with conversation analysis it is possible. Being in the century of customers, the ability for the company representatives to understand the customer, be empathic and deliver fast solution is essential.
Thanks to conversational analysis or text mining, it is now possible to extract data from conversations, to automate and process this data in real-time and at scale. Thus listening to and analyzing conversations helps the representatives to build better relationships and in turn provide customers with the experience they expect.
Sigmaway provides text mining solutions for businesses. Contact us at contact@gosigmaway.com for a proof of concept.
Read more at: http://smartdatacollective.com/calljourney/304151/are-you-listening-your-conversations

Fascinating, the first word that comes to the mind. Drones and big data are bonding pretty well these days and can be a successful recipe for innovations. 

Jonathan Buckley, senior vice president of marketing at Qubole, gives us a glimpse of this promising combo but not without the challenges. 

Agriculture, disaster relief and anti-poaching are some area where the combination has worked wonders. Needless to say more such wonders are in pipeline. But, yes there is a ‘butt’ of challenges attached here. The data gathered by drones is immense, it will require real time big data analytics and ad-hoc analysis to improve. But, one can feel optimistic about the future.

Have a look at  http://smartdatacollective.com/jonathanbuckley/316611/growing-relationship-between-drones-and-big-data

Don't ignore your supply chain risks if you love your profits, that's the advice Keith Peterson, president and CEO of Halo, is giving in his article. He talks about:

• Various supply chain risks
• The department they affect
• Its financial impacts
• Finally! Solution. 

Solution to all the problems these days is in analytics. Right software and analytics programme will increase your profit generating abilities to multiple folds. Intrigued? Follow the link at:http://smartdatacollective.com/keith-peterson/322401/solving-supply-chain-risks-infographic

Internet of Things (IoT) helps in transfer of data over a network without human interaction and this is one of the major sources of Big Data. Tom Davenport, independent senior advisor to Deloitte Analytics agrees that even though the concept of IoT implies that the most important feature of sensors is their connectedness but in order to analyze the data generated and use it for efficient action, analytics is required. This has been referred as the “Analytics of Thing” by him. Compiling data from devices and comparing them across time for achieving best results is one of the principal advantages. Utilizing data to optimize processes, identifying maintenance problems, diagnose anomalies and identifying reason for variations are other things that can be included in the Analytics of Things. Davenport suggests that companies that have to work with fast paced data and have relatively less experience with sensor analytics should invest in The Analytics of Things. Read more at: http://www.tibco.com/blog/2015/05/20/moving-from-the-internet-of-things-to-the-analytics-of-things/

Data analysis conventionally involves a series of process of collecting data from several sources and then analyzing them after some time. Normally these data come with a expiry time i.e. there is a specific short time by which these data needs to be analyzed, processed and utilized. With development in IT world we can no longer wait for data to be collected and then analyzed and processed. The need of the moment is to shift the Big Data nearer to the data source. Thus the value obtained from the data is more important than the way it is collected. Read more at: http://www.tibco.com/blog/2015/04/14/data-analytics-how-to-be-advanced-pervasive-and-invisible/

The success mantra for a perfect digital strategy is to deliver the right message (RM) to right person (RP) at the right time (RT). But we are often overwhelmed by popular trends and forget to look beyond them. Here is an inventory of strategies one can follow to find an optimal solution (might not be the trendiest one). Avinash Kaushik (author) in his blog Occam’s Razor talks about the 5 myths of digital marketing and analytic:

• Programmatic Platforms are a panacea.
• A data first strategy is a winning formula.
• All we need is Facebook, forget our websites.
• The web is dead. Mobile web is dead. Apps are the past present and future.
• Cookies! Cookies are all we need.

For more insight into this piece don’t hesitate to follow http://www.kaushik.net/avinash/digital-marketing-analytics-deadly-myths-de-mythified/

At Paris Air Show 2015, Bombardier plans to bring its CSeries jetliner that carries Pratt & Whitney’s Geared Turbo Fan (GTF) engine which uses great swathes of data. But data created by industrial equipment such as jet engines, gas turbines and MRI machines has more potential business value on a size-adjusted basis which makes it valuable than other types of big data being generated from the social web, consumer Internet and other sources. Finally, the Internet of Things is helping manufacturers manage their Pay by Hour engagement models and long term maintenance contracts at lower costs. With rapid advancements in the Internet of Things in aircrafts combined with data analytics, it’s truly exciting to work in the aerospace industry. Read more about this interesting article at:  http://channels.theinnovationenterprise.com/articles/7319-analytics-and-the-internet-of-things-in-aerospace

In the healthcare industry, big data and business intelligence work as complements which have helped the industry to achieve a remarkable growth. In today’s world data collection has its own advantages but we need instruments to refine them and make sense out of them. Herein lies the importance of clinical and business intelligence. More and more organizations are resorting to business analytics. It helps to make better clinical decisions and organizations stand to benefit from it in the transition from a fee based industry to a value-based one. Organizations have targeted their focus on population health and are implementing C&BI solutions accordingly. These help in deciding on the best strategy for the industry as the care models are undergoing a change. Read more at: http://www.dataversity.net/infographic-business-intelligence-in-healthcare/

Since 19th century, Artificial Intelligence always made everyone very curious but only recently we started to see its applications. Even now its applications are very narrowly limited to natural language processing and image processing. Some people are scared that AI may one day replace humans in many industries and cause unemployment. Let's see what two pioneers in the industry of AI think. Read more at: http://www.technologyreview.com/news/537941/emtech-digital-where-is-ai-taking-us/

Content marketers are delving more into analytics to give interesting insights about their past content. With some careful analysis of this content they are able to come up with new content to meet the needs of their customers. This exercise of tracking the past performance data is important for the content marketers in many ways. Even without analytics, most rigorous analysis and tracking of the data can give information about what to do next. The usage of analytics is giving better pay offs and is the new trend among Content marketers. With the new technologies emerging the usage of analytics tools is expected to make valuable recommendations to help identify the right strategies. 

Read more at: http://www.acrolinx.com/blog/predictive-analytics-content-marketers/

Need a big data solution for your project? The 3 V's of big data will bail you out. In an article by Paul Holland (Consultant), he talks about the 3 V dimensions of big data initially discussed in 2001 by META group (now Gartner) analyst Laney Douglas in a research report. Fourteen years hence, big data challenges and opportunities have acquired 8 V dimensions. The author exclusively focuses on the 3 V's:

• Volume
• Velocity
• Variety 

Volume talks about zettabytes of data generated every second. For example, if we look at airplanes they generate 2.5 billion terabytes of data every year. Velocity is about the speed with which data moves around. Unlike earlier times, data is created in real time or near real time. Variety is basically the different types of data. Gone are the days when data used to fit neatly in tables. Today 80% of world data is unstructured (text, images, videos, voice etc.). Read more at:http://makingdatameaningful.com/2015/05/26/characteristics-of-big-data-part-one/?utm_source=rss&utm_medium=rss&utm_campaign=characteristics-of-big-data-part-one

Digital media publishers have taken their time to incorporate big data tools into their businesses. There have been marked improvements in clarity on use cases for big data and toolsets have also grown accordingly. Big data helps in the content creation side catering to the readers and the advertisers. Keeping the target audience in mind,big data tools optimizes decisions and effectively monetizes generated traffic. Relying on editorial expertise and sound journalistic judgements are fast becoming things of the past. However web analytics softwares like Google analytics, Webtrends also help in tracking content consumption patterns.To know more, please follow:

http://www.dataversity.net/big-data-tools-for-publishers/

Most companies don’t get rid of the currently unused data, with the expectation it may be required to forecast trends in the future. This data becomes ‘dark’ data when the company completely forgets its existence and it becomes difficult to locate it and interpret it or interact with it. However, this ‘dark’ data can be restored or ‘lightened’ up by the following steps:
1. Data filtration, that can isolate the required information in the means of filtering the data feeds, to prevent the accumulation of excess unnecessary data, but is only useful when the data center manager can identify the data, expected to be valued in the present or future times.
2. In case of any future requirement, it is always better to export the data (instead of deleting it) to a cloud-based storage system, from where it is possible to import the data into the company’s data system, whenever required.
3. It is important to properly define, data withholding policies in order to facilitate data center management.

Read more at:http://www.techrepublic.com/article/clear-out-dark-data-to-make-room-for-useful-big-data/

With increasing complexity in the sales environment, improvement in growth and retention of customers is required. Prescriptive guidance can provide answers to these. It is predicted that implementation of analytics tools and strategies will increase. So, B2B companies will reinforce a position for Chief Growth Office (CGO) who will require analytics tools to implement their ideas.
Thus, a step towards Prescriptive analysis and effective implementation plan will help B2B companies to improve their financial performance.
To know more about prescriptive analytics, follow the article written by Javier Aldrete (senior director of product management at Zilliant) at: http://www.inddist.com/articles/2015/05/rise-prescriptive-analytics-b2b-environment

Providing good customer service is a challenge for most businesses and the trends are ever changing. Customers embark on an online journey whenever they buy something. The customer data - a string of emails, conversations across the web and social channels, leave a large digital footprint. Measuring and analyzing this information can help brands narrow down their marketing efforts and investments. Irrespective of the nature of the website, sentiment analysis is crucial. It can tell you whether your customers are frustrated, indifferent, or impressed and suggest measures to that accord. Monitoring customer engagement, referral traffic and time spent on pages can help in understanding the buyers’ journey. Thanks to Big Data, we can work based on intelligence rather than guesswork. Read more at: http://www.forbes.com/sites/danielnewman/2015/06/09/big-data-and-the-buyers-journey-measuring-the-invisible/

The factors currently stressed by predictive analytics, in talent management are:
1. Recognition of potential employees with a flight risk.
2. Recognition of selection factors which can predict the performance of the newly hired employees.
3. Prediction of the productivity initiation time of employee studies.
With the evolution of predictive analytics, new factors that can be expected to be focused on, in the near future include:
1. Projection of the revenue pay-off of a company’s talent programs.
2. Projection of the company’s corporate revenue and labor cost ratio.
3. Projection and comparison of performance indices of a company’s managers, teams and employees.
4. Projection of employee replacement costs.
5. Prediction of upcoming productivity issues and opportunities in the firm.
6. Prediction of the feasibility of new technology solutions.
7. Prediction of diversity bottlenecks.
To know more, visit:

http://www.ere.net/2015/03/09/the-future-of-predictive-analytics-the-next-generation-of-talent-metrics-to-consider-part-1-of-2/

Big Data and Predictive Analytics are booming and Indian recruitment agencies are jumping on board to hire more and more Data Analysts. According to a TeamLease report, the key trends that will dominate the recruitment industry over the next six months include Information Technology (IT), engineering. It is also predicted that startups will be key hirers and adoption of Recruitment Process Outsourcing (RPO) will increase. The nation is quickly realizing the importance of Big Data and Predictive Analytics and both large companies and start-ups are beginning to employ Data Analytics into their workings. The fields where Data Analytics will primarily be required include market risk analytics, facility management and mobile applications employing data sciences. Read more at: http://timesofindia.indiatimes.com/business/india-business/Big-data-and-predictive-analytics-likely-to-dominate-recruitment-TeamLease-report-says/articleshow/47588357.cms

Health insurance carriers are currently in a dilemma, whether to purchase an analytics platform, assemble a platform and then use it. Lack of proper infrastructure is a big hindrance for analytics in healthcare system, dominated by paper-based transactions and the dearth of their electronic imprints. Since health contracts are based on the payment of money, depending upon the health status of patients, health insurers have an incentive to build an analytics platform. Currently, the healthcare insurance companies, who are willing to purchase analytics platforms, have limited options to choose from. While options are being worked upon, healthcare insurance lags behind property and casualty carriers, who are not restricted by intricate security measures and government hindrance. Read more at :

http://www.insurancetech.com/2015-outlook-analytics-in-health-insurance/d/d-id/1318241?

Sigmaway consultants have worked with clients in benefits solutions workspace providing analytics on healthcare plans. For more details visit

http://www.sigmaway.us/