Big data and analytics projects will be managed by individual departments when the analytics solution at hand concern to a specific function that department does. The analytics solution is required to answer key questions that about the business, whether it is struggling with in a particular area of expertise or not. This makes the owning department the most logical area to start the search for an analytics solution. Some good practices can be: i) develop a compelling business case for the application ii) Get support for the project. iii) don't let IT run the project iv) Trial the new application v) Perform due diligence vi) Develop a roadmap vii) Don't let the technology take over viii) Create a super user ix) Always attempt for a "quiet" system. Read more at: http://www.techrepublic.com/article/10-tips-for-running-a-successful-analytics-project-outside-of-it/

The internet has now become an important part of our life. Looking at the past, we can see how the internet has developed over the years and made our lives faster and connected. But there are a number of problems that we need to solve for maintaining what we have achieved. Biggest Issues: i) Global Inconsistencies in Internet Availability ii) 30-40 % Annual increase demand for Bandwidth iii) Unexpected Fluctuations in use iv) Cybercriminal Access because it's available to all, so more potential targets v) Overreliance on Major corporations vi) Patchwork Fixes. It requires collaboration from multiple industries and multiple companies, from major internet providers to tech companies and even governmental organizations to make the infrastructural and cultural changes necessary to improve the internet's future.Read more at: http://www.datasciencecentral.com/profiles/blogs/the-6-biggest-internet-problems-we-need-to-solve

A decentralized network help banking database connecting unique chain to store transaction records. The technology allows the database to bypass the disruption of the payment network that are often slow, cumbersome and expensive also help in making strong fraud to die out from the system. The financial banks taking up the bonds and shares to get replaced in a decentralized structure. Furthermore, the middlemen are cut through the technology, moreover, it also cuts the cost of transaction records. Looking towards the new area of transformation the bitcoin technology is far approachable to adjust the use of database in decentralized form. Read more at: http://analyticsindiamag.com/blockchain-technology-the-immutable-database-revolution/

The basic premise behind the IoT is to connect everyday objects to the internet through tiny sensors, allowing them to communicate with businesses, consumers, and each other.

While hearing about the Internet of Things doesn’t necessarily signify a consumer would not use an item connected to the IoT, the survey results show a lack of awareness and understanding about what can be gained from it.

The Internet of Things sounds good in principle, giving consumers unparalleled convenience and access to the latest technology, but there is one requirement that can’t be ignored: the internet.

One idea for the Internet of Things is to place sensors on roads, traffic lights, utility grids, and buildings, but doing so represents an expensive venture.

Read more at: https://www.smartdatacollective.com/potential-hurdles-limiting-internet-things/

Software robots are playing an increasing role in workplaces. Robotics helps in improving productivity of the employees. America, at present, is the largest market for RPA (Robotic Process Assistant). RPI is a great fit to the Banking, Financial Services and Insurance sector. RPA has great market potential, but as of now, it has less than 5% share of the total potential share. The most important point is that the RPA will not replace humans completely, but it is likely to provide relief to humans from repetitive, manual and monotonous work. Read more at : http://www.cxotoday.com/story/robotics-in-the-workplace/

There are many challenges that are faced by marketing executives as well as compliance leaders in emerging markets with increased corruption and risks. Each country has unique sets of market opportunities and risks and cannot be transferable to separate market. Markets are also dynamic and applying the same outdated models might give inappropriate results. Strategic intelligence is the need of the hour, with updated market intelligence and multiple data sets. This updated market information would account for changing market conditions.There should be a right mixture of centralized and remote market intelligence and MNC's should extract information from various sources. Finally, there should be a mutual collaboration and sharing of responsibility between compliance and market intelligence leaders. Read more at : https://blogs.metricstream.com/can-marketing-compliance-share-playbook/

Fast data is the application of big data analytics to smaller data sets in real-time in order to solve a problem or create business value. The goal of fast data analytics is to quickly gather and mine structured and unstructured data so that customer experience can be improved by creating a more streamlined process for marketing strategies and customer service implementation. It has been observed that fast data analytics helped businesses turn their raw machine data into actionable insights by tracking transactions, identifying issues with hardware and software, and reducing customer complaints. It also helped in staying compliant with government regulations, avoiding preventable losses and improving the personnel’s efficiency by pinpointing errors. Thus, fast data analytics services significantly improve business’ customer experience by solving issues faster and more efficiently. Read more at: http://www.datasciencecentral.com/profiles/blogs/how-you-can-improve-customer-experience-with-fast-data-analytics?xg_source=activity

There are many challenges that are faced by marketing executives as well as compliance leaders in emerging markets with increased corruption and risks. Each country has unique sets of market opportunities and risks and cannot be transferable to separate market. Markets are also dynamic and applying the same outdated models might give inappropriate results. Strategic intelligence is the need of the hour, with updated market intelligence and multiple data sets. This updated market information would account for changing market conditions.There should be a right mixture of centralized and remote market intelligence and MNC's should extract information from various sources. Finally, there should be a mutual collaboration and sharing of responsibility between compliance and market intelligence leaders. Read more at : https://blogs.metricstream.com/can-marketing-compliance-share-playbook/

 IBM announced last week it has moved its cognitive computing system into the cloud to form the Watson Discovery Advisor, allowing researchers, academics and anyone else trying to leverage big data the ability to test programs and hypotheses at speeds never before seen.

"I think there have been a number of ways that we have improved the system since Jeopardy", said John Gordon, vice president of IBM Watson Systems.

IBM has been honing Watson's capabilities over the last three years, reducing its size and upping its power since its famous appearance on "Jeopardy!" in 2011.

"Part of Smarter Cities was working with different municipalities and governments to determine how technology could help them provide better services to their constituents", Gordon said.Read more at: https://www.fedscoop.com/watson-cloud/

Social media analytics or SMA, is the practice of gathering data from social media websites and analyzing that data to make business decisions. The most common use of social media analytics is to mine customer sentiment to support marketing and customer service activities and turns the vast amounts of semi-structured and unstructured social media data into actionable business insights. Depending on the business objectives, social media analytics can take four different forms. The first two are reactive in nature, while third and fourth are proactive in nature. First is descriptive analytics. Descriptive analytics gather and describe social media data in the form of reports, visualizations, and clustering to understand a well-defined business problem or opportunity. Second is diagnostic analytics, it can distill this data into a single view to see what worked in the past campaigns and what didn't. Third is predictive analytics, it involves analyzing large amounts of accumulated social media data to predict a future event. And the last one is prescriptive analytics, it suggests the best action to take when handling a scenario. Read more at: http://www.analyticbridge.com/profiles/blogs/4-types-of-social-media-analytics-explained

Career opportunities in the technology sector are increasing. Technological sector, like any other sector, needs employees in finance, marketing, sales and human resources. In case of a transition in career, an experienced field can be chosen. Knowledge and skill never go to waste. Four career transition tips are mentioned here. 1. Focus on soft skills because no matter what sector you work in, it is a key factor. 2. Use networks to make connections in the sector. 3. Do your homework and gain knowledge in your field. 4. Identify and prepare a narrative of your strengths that will be useful to the sector. Read more at: https://www.forbes.com/sites/davidkwilliams/2017/06/04/making-a-career-transition-to-technology-its-not-rocket-science/#98ef669474c7

All organizations face pressure to improve performance. This is difficult as there exists risks which reshapes the businesses. As the risks become more intertwined, managing them becomes difficult and leads to chaos. GRC helps the businesses to achieve task of managing everything under one umbrella. GRC helps simplify the complex and huge data. Most businesses are implementing AI systems to speed up the investment decisions. Systems will be able to automatically collect data from various data streams and channels. Also analyze it against the company’s existing datasets and operations, making suggestions regarding the changes. As technology evolves, algorithms improves and probability of errors reduce. Cyber risk is a new threat. As companies face greater pressure a more advanced GRC technology is to be adopted. Read more at: http://www.itproportal.com/features/the-road-ahead-the-coming-rise-of-artificial-intelligence-in-governance-risk-and-compliance/

The present business environment is volatile and full of uncertainties. Therefore, a need arises to improve efficiency and profitability. Though many organizations rely on traditional techniques, predictive analytics is the new trend of managing risks and monitoring frauds which eliminates all the guesswork. Predictive analytics help us in reaching the source of fraudulent transactions and in dealing with future plausible attacks. Lack of corporate transparency and missing public trust should be dealt with by using advanced tools for managing huge data and ensuring accountability. Predictive analytics helps in building the customer profile to know his credibility which is useful for banks. Read more at : https://blogs.metricstream.com/ready-predictive-analytics-revolution/

The data scientist focuses their efforts on developing analytics solutions that solve a specific and unique business problem. The primary reason for this declining demand, according to the author was that increased automation and operationalization of business processes will not require the technical skills of the data scientist. IT individuals steeped in the more traditional computer science discipline are trained and developed to focus their skills on developing solution that streamline business processes. Creating a technological environment which allows access to data and the potential for increased automation is the role of IT. This kind of scenario is simply going to increase the demand for both data scientists and IT in our Big Data world, regardless of certain opinions on the declining importance of data science. .Read more at: https://www.smartdatacollective.com/demise-data-scientist-heresy-or-fact/

From gyms to the front desks of Medical practice center, analytics are used everywhere. Most of the sectors have been semi-automated. Some small businesses, however, have failed to use analytics. Except these exceptions, most of the businesses have been successful in combining data science and cloud technology. Data analytics are essential for medium and small scale companies as well to be successful and data centric transformations are now trending. Read more at: http://www.zdnet.com/article/using-analytics-for-health-commerce-and-more/

Consumer Intelligence is largely focused on improving customer behaviour and enhancing consumer products which are tailor made to match consumer expectations. AI helps industries to introduce new product features by finding patterns in huge datasets. There are two types of categories in consumer AI : front end bots and AI assisted human agents. Chatbots take care of customer text queries. AI in enterprises has been useful in Enterprise Resource Planning. Enterprises are conducting predictive analytics in developing AI applications. Enterprise AI can be of two types- Applied AI and Artificial General Intelligence. Though comparing these two enterprise AI is complex and requires much more expertise  than consumer artificial intelligence. Read more at: http://analyticsindiamag.com/enterprise-ai-vs-consumer-ai-understanding-two-differ/

Random forest is an ensemble classifier that consists of many decision trees and outputs the class that is the mode of the class's output by individual trees. It is called random because there are two levels of randomness; at row level and at the column level. In spite of it being such a convenient process to deal with large datasets it has a few disadvantages. In case of smaller datasets linear regression is a better method than this. Next is that any relationship between the response and independent variables can't be predicted. Also, this process is very cumbersome and can't take values from outside the datasets. Even then, random forest is advantageous because keeping the bias constant it can decrease the variance in the datasets and it helps us ignore most of the assumptions like linearity in datasets. Read more at: http://www.datasciencecentral.com/profiles/blogs/random-forests-explained-intuitively

It’s no secret that President Trump prefers tweeting over talking to the public — particularly when nearly everyone else in the country is fast asleep.

Trump’s Twitter archive shows that some of his angriest and most flamboyant accusations are issued early in the morning.

For most people, the middle of the night and the very early morning are not great times to make decisions, to say nothing of making policy pronouncements or political commentary.

At those times, you are likely to be close to so-called REM or dream sleep, which we all know brings about intense and often distorted emotions and thoughts, often about the events in our everyday lives.

These are times for reflection, not for social media.

A bit of unsolicited medical advice for President Trump: For the sake of the nation, stop tweeting and go back to bed.Read more at: https://www.nytimes.com/2017/06/05/opinion/mr-trump-stop-tweeting-sleep-deprivation.html?rref=collection%2Ftimestopic%2FSocial%20Media

Records were exposed globally, killing security running for support. A wannaCry attack leaves hints to the user on a network system. Moreover, how the security is protected or responsible by the fact of undercovering its data and information more strongly not be damaged to expose, also how the data miners are fighting against these cybercrimes. AI refining the threat of cybercrime and developing more ideas and innovation to counter such attacks. Not only that AI and quantum computing are challengers, but also a way with uncertainties. Read more at: https://www.ft.com/content/1b9bdc4c-2422-11e7-a34a-538b4cb30025

Price Transparency Tools provides many options to select the required services. It helps customers to reduce medical costs. Statistics say that the proportion of moderate income community group is more likely to use this tool as compared to higher income community. Thus, the aggregate spending is still high. Consumers who are good with internet mostly use this tool. Thus, it should be marketed properly so that it reaches out to a larger number of people. Sending out reminders is a great option to start with the process. Read more at : http://www.healthcarefinancenews.com/news/healthcare-price-transparency-tools-seldom-used-study-finds-more-reminders-marketing-needed