Permission marketing is now trending. Consumers don’t like to get interrupted often and so they take actions to block online ads, promotion emails. This new era of permission marketing can be broken down into “anticipated”, “personal” and “relevant”. A recently concluded study shows customers are willing to share information with trusted brands. Data privacy acts now protects consumers from personal data collection through websites and other online sources. Cookie law is such an example. Customer data can be explicit, implicit or structured by analytical tools. Thus data security is of utmost importance and it is the responsibility of organizations. Consumers are always looking for their needs to be met by companies and this gives the companies the chance to make the best use of data collected providing value to the organization. Read more at: http://www.cmswire.com/digital-marketing/tracking-customer-data-you-better-provide-value/

Today, fast and accurate decisions are critical for an organization's success. But there is a risk of incorrect decisions if we rely on approximate sciences such as intuition and judgment of individual decision makers. The value of data can be realized only once a coherent ‘data strategy’ is established. A data strategy requires an organization to embed and integrate data analytics into the process of decision-making. The organization must seek and utilize data based insights that are most fruitful. Big Data demands a tighter integration of business functions and better mechanisms for integration. Evidently, various teams shall work together to understand and exploit cross-functional data. Identifying key data gaps and taking collective decisions for data gathering will ensure that specifically data with potentially useful information is collected. Read more at: http://www.bobsguide.com/guide/news/2015/Jul/13/big-data-small-data-and-fast-data-using-data-to-drive-better-decisions.html

As researchers and scientists get access to the plethora of information of weather patterns, they are getting better equipped to deal with upcoming disasters. This data however is massive and highly complex thus the data gathering serves as only a part of the solution. Governments today are realizing the need for data-driven forecasting to keep up with the volume and variety of information required for smarter forecasting. Predicting weather anomalies more effectively could save thousands of lives during natural disasters. The process requires delivering more accurate forecasts and delivering them sooner. Data analysts use the voluminous data gathered to develop reliable forecasting models. Making sense of the data and building actionable intelligence will largely help protect the public from natural disasters. Read more at: http://www.forbes.com/sites/centurylink/2015/07/08/hurricane-forecasts-get-better-give-more-warning-thanks-to-big-data/

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

Starting off as a small time entrepreneur it might be difficult to see the use of Big Data for your company’s growth. After all Big Data seems to be a term befitting multi million dollars firms, not for start-ups. In reality this isn’t true. Your small start-up can grow exponentially at a affordable cost using data resources which can be availed online by almost anyone.
Here are a couple of ways how it can work for you.
Customer Relationship Management (CRM):
A very important resource for any business is CRM software. Owners can set up a simple CRM spreadsheet, even if it’s just one single webpage, lets you to grab your customer’s feedback which helps towards your company’s growth.
Marketing:
As a small business owner you cannot afford to waste your valuable resources on a  misplaced advertisement or trying to market your product when there is no demand for it. You can use Big Data to analyze the market trends to key in on when and where buying habits are highest.
Big Data is everywhere and you can make use of it easily as long as you keep it simple & streamlined and not overdo it.

Read more at: http://www.smartdatacollective.com/keithtullyy/322521/how-small-business-can-use-big-data

It depends on the enterprises' ability to find value in IOT generated data and come up with metadata fabric that enables efficient data analysis. Metadata fabric works in sync with IOT to benefit the enterprise. It can be viewed as the storehouse of business intellectual property. It makes data driven decisions a lot easier. Metadata fabric transforms unified interpretation of data and analytics into layman format and interface easily understood by businesses. IOT ecosystem often throws challenges as the number of unique data sets collected is smaller than the number of applications that need it. Introduction of an intermediate curation layer can solve this governance problem. The aim of the governance system should be to reduce onboarding cost with increasing chances of success. Optimization should also check for homogeneity in the collected data. To know more, please follow:

http://www.dataversity.net/data-governance-the-metadata-fabric-and-the-internet-of-things/

Big Data may be relatively new but data has been a hot topic of discussion for over a 100 years. Interesting to note, the challenges in fetching and understanding it remain fundamentally the same. We are told that this is the era of Big Data but its roots go back to 1914. Willard Brinton wrote the first book on communicating data, Graphic Methods for Presenting Facts. He had stated that those who possessed cutting-edge data technologies would be the pioneers in their field. Processing and visual representation of data as information would allow us to give just the required information and facts to allow those who aren't proficient in data, actionable insights into their problems. In 100 years more, we would hopefully understand analytics and effective data visualization. Read more at: http://www.computerworld.com/article/2942728/big-data/big-data-the-100-year-old-buzzword.html

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

Banks, when adopting a mobile-first strategy, should look beyond mobile apps. To achieve a successful mobile-first strategy, banking sector should deploy data analytics. Although several tech giants are threatening traditional banks with their mobile enabled financial services, banks possess certain advantages. They are a trusted source for financial services and have maintained long-term relationships with millions of customers. Banks possess a wealth of customer data, transactional data to be specific, which can be leveraged to gain insights on customers. This will help banks to understand customer behavior and target their behavior. Read more at: https://channels.theinnovationenterprise.com/articles/7649-banks-are-pioneering-the-mobile-revolution-but-can-they-see-beyond-the-app

Big data can also be applied in the field of humanities specially history. With advancement in text analytics, historians can now go through a huge number of historical documents and discover patterns and trends from the past. These then can be used as evidence to check if theories are correct. Research students analyzed a huge number of novels using big data analytics which allowed them to leverage insight on what the semantics implied about the society. Given the nature of historical documents, it is difficult to digitalize and apply text analytics to those. Thus data analytics is being considered by historians now. Big data when applied to history will help bring information scattered over the world thus helping historians to gain insight and predict the future. Read more at: https://channels.theinnovationenterprise.com/articles/data-looking-at-the-past

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 social mention, which is a search engine which searches any social mention of the topic in social media there are other tools such as quora, tweetreach, etc. 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

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/

Data analytics is no longer limited to the field of business and market research but it has spread across the financial sector as well. Stock market investors are using data driven insights and predictions to make crucial investment decisions. By observing the market conditions and various metrics related to it, the data scientists are being able to come up with accurate inferences about the market, and the data analysis is becoming increasingly precise and data intensive.  This is due to the availability of financial data and decreasing cost of information technology. The growth of analytics in this sector is likely to continue and is going to revolutionize the way financial trading is done. To know more read: http://www.huffingtonpost.com/irene-aldridge/why-big-data-matters-in-f_b_7553438.html?ir=India&adsSiteOverride=in

The healthcare sector is now exposed to data breaches as it has adopted the online mechanism, for maintain health records or say for remote patient monitoring. Data breaches are not only expensive in terms of costs incurred by the healthcare provider but also in terms of patients' lives. Data analytics helps in interpreting unstructured data, which may help to prevent not only data breaches but also (say, medical prescription) frauds.  Big data analytics allows organizations to amalgamate and analyze their data irrespective of the source, type, size or format and finally understand the patterns needed to address fraudulent activities. Again, by updating, pharmacies, doctors, and hospitals on data insights, concerning substance history information of patients, it is possible to take better prescribing decisions and identify potential prescription drug abuse. Read more at: http://venturebeat.com/2015/03/31/big-data-analytics-can-prevent-health-care-fraud-heres-how/

Sigmaway consultants have worked with clients in benefits solutions workspace providing analytics on healthcare plans. For more details visit http://www.sigmaway.us/

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/

The emergence of analytics in business has also contributed extensively in the field of talent management. Talent analytics has become an important area in both consulting firms and corporations. Not only it helps in acquiring and attracting new talent but also helps in talent utilization and maximization of organizational performance. In earlier days talent management was done by managers who trust their “intuition” or “common sense”, which led to bias and wrong decisions. But thanks to the development of information technology and availability of expertise in the field of data analytics, talent management is following a scientific path and a better system of workforce management.To know more read:

http://www.forbes.com/sites/edwardlawler/2015/05/20/talent-analytics-old-wine-in-new-bottles/

Growing social networks have caused rapid development of tools for understanding the interactions between members of the network. The Department of Computer Engineering, at TOBB University, in Ankara, Turkey used Social Network Analysis (SNA) tools to identify the biomarkers present in patient genomic data. Genomic databases comprise of about 20000 genes. Such an approach dramatically decreased the features that need to be analyzed to find useful biomarkers. The team demonstrated their proof of principle with three types of cancer: lymphoma, colon cancer and leukemia. They combined clustering and classification to help in detecting the links between the various genes to validate the outcome. Now they shall extend it with a view to improve diagnostics and tailoring therapy for individual patients based on their personal Biological Network Analysis. Read more at: http://medicalxpress.com/news/2015-06-social-networking-analysis-cancer-biomarkers.html

Data analytics with its growing importance is now used to plan mergers and acquisitions which require a well thought game plan. Throughout the buying process, data analytics can be used to see how market will respond to a deal being made. While merging with another company, data gets doubled and so it is important for employees to analyze all sets of data thus allowing business users to make better decisions. All through the M&A process employees must be trained to possess analytical process, needed to survive in this data-driven economy. Organizations must be aware of how effective and intelligent data management and analytics can help drive Mergers and Acquisitions win. Thus Big Data can offer success to M&A. Read more at: https://channels.theinnovationenterprise.com/articles/7467-the-big-data-game-plan-in-mergers-and-acquisitions

When it comes to Data Analytics, failure is a very important part of the innovation process. A part of the data scientist’s job is trial-and-error and assumptions to vet data for new insights. Pushing the analytical process to uncover new uses of data and new ways of applying analytics necessarily involves risk and failure. Leading websites embrace this by testing hundreds or thousands of both minor and large scale changes to their site daily. Nothing is rolled out broadly on a major website today unless it has gone through rigorous testing. An organization based on rapid experimentation, exploration of new ideas and educated in doing analytics right is one destined to succeed. Read more at: http://www.forbes.com/sites/teradata/2015/05/27/why-being-wrong-is-the-best-way-to-get-your-analytics-right/