Machine Learning (ML) will have a big impact on economics as it helps in taking properly calculated decisions. The ML methods can be modified to make them fit for using in econometrics. These reduce the risk to failure. Data is the key to success for this. Based on the previous records, a model can be trained. Economists are being increasingly interested in technology. ML can help in clarifying the real situation from what is being assumed. Many technical firms are hiring economists. The mix of proper proportion of technology with the knowledge of economists will definitely lead to great results. Read more at: http://www.forbes.com/sites/quora/2016/01/27/what-will-the-impact-of-machine-learning-be-on-economics/#5bccf597ad5e

Ever wondered if machine learning can be used for Data Driven Marketing. The Intelligent Agent (IA) developed on the concept of machine learning takes a big leap in data driven marketing.  IA technology can learn about the user behavior and suggest most suitable actions. It can identify the most relevant data from the whole lot and can even find out the reasons for the importance or relevance of that data. Artificial Intelligence is revolutionalising the field of marketing. Intelligent Agent would reduce the manual processing and will produce better results. Read more about it in the article written by John Bates(Senior Product Manager for Data Science & Predictive Marketing Solutions) at: http://blogs.adobe.com/digitalmarketing/analytics/data-driven-marketing-ready-for-machine-learning/

A lot is investment is made in the digital marketing campaign. Before planning the campaigns, it is important to correctly determine whether to use Rule Based or Algorithmic Attribution. First, we have to analyze the data in hand properly. If the data is coming from different platforms and needs to be combined or analyzed at one platform, then Rule Based Attribution can't be even thought of, go for the latter. Rule Based Attribution uses the last touch as the final touch, so sometimes it can be misleading. If the journey to the destination has been maneuvered by the smart moves at each step, then we can't rely on the Rule- Based approach. But if the algorithmic approach was that easy, everyone could have adopted it. Read more about the pros and cons of each in the article written by Matt Scharf (Senior Manager at Display Media Operations & Analytics at Adobe Systems) at: http://blogs.adobe.com/digitalmarketing/analytics/rules-based-vs-algorithmic-attribution/

The fast growing field of "wearables" has brought in one amazing technology. This is being called as "disappearables". The logic behind this is to make technology modest. The wearables should capture energy from the surroundings, sense and observe the environment around. But the challenge for the wearables manufacturing companies is to produce cost efficient products. These should not be restricting the body movements or shall not have the consistent charging issues. This new technology is called disappearables because the user itself can't tell whether he is wearing the smart wear or not. Read more about this amazing technology in the article written by Ben O'Brien (Contributor) at: http://www.entrepreneur.com/article/254301

Hadoop and Apache Spark are seen as the competitors in the world of big data, but now the growing consensus is that they are better convention in together. Here is a brief look at what they do and how they are compared.  1. They do different things: Both are the big-data frameworks, but they do not serve the same purposes. Hadoop is a distributed data infrastructure. It also Indexes and keep track of that data, enabling big-data processing and analytics. On the other hand, Spark is a data processing tool. Secondly, both can be used individually, without the other. 3. Spark is faster 4. You may not need Spark's speed: Spark is fit for real-time marketing campaigns, online product recommendations, cybersecurity analytics and machine log monitoring. 5. Failure recovery: differently, but still good. Read more at: http://www.computerworld.com/article/3014516/big-data/5-things-to-know-about-hadoop-v-apache-spark.html

The purchasing decisions taken by the customers are more often the result of online reviews and various comparisons. After buying products they themselves become reviewers and express their views on web about the product. This significantly impacts the reputation of the product and hence the company. This expands marketing horizons, thus its measure can't be only limited to ROI (Return on Investment). Work of marketers is not limited to being just creative. It is important for them to be contributing employees to the organization. Testing of the marketing strategy should be done. All the influencing factors should be kept in mind. The marketing team should be aware of when to measure. Read more at: http://bloomreach.com/2016/01/measuring-marketing-roi/

Before you approach a marketing automation vendor, there is always some necessary groundwork to do. This is not only important to prevent making fool out of yourself, but also to get best out of the vendor. A vendor can only provide what you want, if you have 100% clarity of it. It is important to highlight your needs. Add-ons are always good if they make your work better. Keep the strengths and drawbacks of your old system in mind. A clear goal must be decided before starting the automation. Read more about it in the article written by James A. Martin (tech journalist and bloggerz) at: http://www.cio.com/article/3023570/marketing/12-questions-to-ask-marketing-automation-vendors-before-you-buy.html

E-Commerce firms very well understand that data is a wealth. The data can provide very crucial and meaningful insights, if used properly. Data Mining is one such way. It is a field of computer science that discovers the patterns in large data sets. This is done using the methods of Artificial Intelligence, Machine Learning, Statistics and Database Systems. Algorithms are made to act on the data set. This often reveals "game changing" results for the industry. Data Mining can be either done manually or can be automated. E-Commerce Firms use this to get to know more about customer's emotions, preferences, and other factors that impact their purchasing style. So they excel in offering a personalized experience through this. It doesn't stay limited to customers. Data Mining is done to keep an eye on the competitors. Read more about it in the article written by Arie Shpanya (contributor to Econsultancy)  at: https://econsultancy.com/blog/67360-why-data-mining-is-the-future-of-online-retailing/

Before we start discussing about Tools for Social Media Analysis, first of all we have to know what social media analytics is? Instead of thinking it as a noun, take it as a verb. Precisely, it's gathering data from social platforms to help guide marketing strategy.

# the process begins with the prioritizing goals.

# The second step is determining key performance indicators (KPIs) i.e. likes and shares your posts receives, replies and comments, and more importantly the clicks your links and content earn analysis.

Now, as the definition is clear, we will directly come to the social media analytic tools. To read more, follow: https://keyhole.co/blog/list-of-the-top-25-social-media-analytics-tools/

It's no more difficult to shop at a new place with Location Based Marketing. We often look for the unique and best products, when we visit a new place. A common practice is to inquire about the best deals, with the people around who are aware of the new place. But with everything becoming techy we have Location Based Marketing to rescue. It integrates mobile marketing with location based services. The motive behind this is to make mobile users aware of your presence, while they are in the areas nearby. Most relevant display ads as per user's location are sent. Their interest can be pulled by either providing some discounts or some other perks. This benefit both the user as well as the business. Read more about it in an article written by Jack Simpson (a Writer at Econsultancy) at: https://econsultancy.com/blog/67418-what-is-location-based-advertising-why-is-it-the-next-big-thing/

Finding suitable talent for your workplace is a difficult process. It is much more difficult to retain talent, if the workplace conditions are not suitable. Most of the organizations use annual feedback system to know about the employees. But the better way is to have a continuous check on the performance and behavior of employees. This helps in getting a better picture. Big Data helps in identifying the relation between engagement and retention. Cloud based solutions provide access to all the data at one place and this can be used for further decisions by HR. Data can be collected, measured, analysed at one place. And accordingly solutions can be thought of to eliminate the problem. Organizations who use big data solutions have observed a better turnover. Read more at: http://www.cio.com/article/3023311/careers-staffing/how-big-data-can-drive-employee-engagement.html

We've been thinking about the Internet of Things all wrong. According to various predictions by various companies, there were various statements specifying volume and amount of money, number of connections. These are just numbers, Numbers, more numbers. If we believe in the predictions, there is no way that current analytical solutions can manage that level of information. In the immediate future artificial intelligence capabilities are required. Which means all companies who have an analytics platform play will have to invest in A.I. research, acquire and finally emerge with solutions based on methods beyond machine learning. Or risk being left behind. If this sounds vaguely familiar, it's because right now all efforts are pointing towards machine learning and algorithms as the goal for analytics. To read more visit on: http://www.forbes.com/sites/theopriestley/2015/12/08/a-series-of-unfortunate-tech-predictions-artificial-intelligence-and-iot-are-inseparable/#39f25ec8523a1253d985523a

The trend of wearables is growing hotter each day. BYOD (Bring Your Own Devices) and IoT (Internet of Things) clubbed together, is adding more efficiency and flexibility. It's no surprise that smart wearables are already passé for fashionistas. On the counterpart, these trends are attracting the attention of hackers. Wearables are being profoundly used for both business and personal purposes. Thus making them a rich source of information. This could act to the disadvantage if the information gets into the wrong hands. Though the wearables have not revealed any big disadvantages, so far. But as always, with evolving technologies, there always exist weak points. The hackers find these weaknesses and exploit it to their benefit. So it is essential to do proper research on the wearable, before handling it a prominent portion of your information. Read more about it in an article written by Jen A. Miller (a freelance journalist) at: http://www.cio.com/article/3022059/wearable-technology/how-secure-are-wearables-anyway.html

The Internet of Things (IoT) is impacting on consumers’ lives and corporate business models. It is increasing at the rapid rate and by 2020, more than half of the major new process will incorporate some element of the IoT. IoT is basically connecting device with an on and off switch to the internet. By 2020, a black market exceeding $5 billion would exist to sell fake sensor and video data for enabling criminal activity and protecting personal privacy. To address this compromises in IoT security will have increased security costs to 20% of annual security budgets. To read more visit on:  http://tech.firstpost.com/news-analysis/by-2020-more-than-half-of-new-business-processes-will-incorporate-some-element-of-iot-says-gartner-295467.html

We all are aware of the revolution brought by the cloud computing in today's business functionality. The management and storage of big data in cloud is well known to everyone. One of the best outcomes of cloud based solutions is the Hosted VoIP technology which is changing the way we communicate. On an average, 7 out of 10 telecom customers still do not understand what Hosted VoIP is. In short, VoIP is the concept of using the internet and cloud based servers to place calls instead of using traditional PBX boxes and phone cables. The same concept applies to telecoms solutions built on a larger scale. Irrespective of the type of business Hosted VoIP is beneficial to all. To read more about Hosted VoIP visit at:http://www.smartdatacollective.com/josh-rose/367715/72-people-aren-t-familiar-hosted-voip

Drop shipping refers to the direct delivery of the products from a manufacturer to the retailer or the customer. This is very convenient if you are going to start an ecommerce business. This decreases the overhead as the costs of purchasing inventory or managing warehouses is eliminated. The businesses using drop shipping find scaling easier. For example: if you receive four times as much offers, you'll usually need to do four times as much work. But with drop shipping most of the work to satisfy the additional orders is to be done by the suppliers. This makes businesses flexible. Most of the startups find difficulties in raising funds. So, it is easier to start with drop shipping. It even offers the largest variety for the customers. Being directly linked to the manufacturers selling the products, number of middlemen decreases. Fewer the middlemen, bigger the profits of a business. Read more at: https://econsultancy.com/blog/67406-what-is-dropshipping-and-is-it-right-for-your-business/

Firms often spend a huge amount of money on display marketing. But as a consumer, do you remember at all the last display ad you saw. The answer is NO. Display Marketing can be very effective if targeted. It is important to know which item should be placed on which site and what part of the site. Most vendors don't go into details of the strategy, thus shelling out more money out of those interested in display marketing. Algorithmic attributions can be used to determine how the impressions will impact the ROI. Learn more about it in the article written by Sandy Martin (Sr. Business Consultant) at : http://blogs.adobe.com/digitalmarketing/analytics/how-to-get-more-from-display-marketing-with-analytics/

A system outage is worse than a nightmare for the IT managers. Downtime is when, the system on which your business relies is dead, down or unavailable. In spite of any levels of preparation, this problem is faced by most of the organizations. And the recovery period builds astronomical pressure on the IT team. A report suggests that the majority of the system outages is due to ill planning. System Outages lead to huge revenue losses each year. Downtime affects the reputation of the business firms significantly. Read more about system outage at: http://www.evolven.com/blog/downtime-outages-and-failures-understanding-their-true-costs.html

Cybersecurity is a very important and is becoming one of the biggest worries for companies. According to various surveys, companies are investing a lot of money in cyber security and training their employees in it. It is estimated that till 2020 investment in the cybersecurity will be around $170 billion. In today’s world as the data is rising, so the risks on it are also increasing. The pattern classification systems that machine-learning algorithm rely on themselves exhibit vulnerabilities that can be exploited by hackers. As we know machine learning algorithms train themselves with the training data set so it may be manipulated according to the needs as hacker wants. For example, Search-engine-optimization algorithm was trained and manipulate website content to boost results in the search ranking or senders of junk emails try to fool spam-filtering algorithm. Even the results of the public election can also be affected by 20% or more as it is found that the order in which candidates appear in search results can have significant impact on perception. To read more about Cybersecurity risks, follow the article by Dr. Kira Radinsky (CTO and Co-founder of SalesPredict) at: http://blog.kiraradinsky.com/author/kiraradinsky/

Predictive models are used to predict future outcomes on the basis of data collected from past. Many organizations take their crucial decisions based on the foundations laid by the predictive models. But what if the model goes wrong? "BOOM"- crash of a significant part of the strategy! Though each predictive model has some scope of error. There are chances that the input variables considered for the model were not appropriate. But we need to find out what kind of error and to what extent it is acceptable. There is a need to work on the foundation of the predictive models to prevent failures.  Read more about it in the article written by John Bates(Senior Product Manager for Data Science & Predictive Marketing Solutions) at: http://blogs.adobe.com/digitalmarketing/analytics/what-to-do-when-your-predictive-marketing-is-wrong/