Corporate Training Analytics

From automation to smart office gadgets and chatbots, artificial intelligence has today become increasingly prominent in the workplace. As smaller organizations see their major competitors taking advantage of AI and machine learning, they've understood they require to jump on the bandwagon to keep up -- but they might be thinking how they'll be able to afford it. Luckily for organizations on a budget, you don't require to break the bank to begin integrating AI and machine learning (ML) into your operations. By initializing on a smaller scale with ready-made solutions, you can leverage the power of AI and ML, and enhance your business performance. Here are the few ways through which you can incorporate Machine Learning in your enterprise. 1.Leverage Existing Platforms Creating your own AI is quite complex and expensive- but it doesn’t mean it can’t benefit you. Several big organizations such as Facebook and Google have open-sourced their own AI endeavors, making it pos...

Modern organizations realise the tremendous potential of machine learning and AI but at the same time are struggling to draw valuable insights from the massive amount of data they generate and save every day. Machine learning, the field of computational science centred on pattern recognition is playing a very important role in our daily lives. We can find everyday examples of machine learning in action right from suggestions offered by Amazon and Netflix, pre-approved credit card offers, saving and investment offers from your bank or for that matter Apple’s Siri, machine learning continues to make our lives simple and convenient. One thing in common among all these is the creation of predictive intelligence based on historical trends. To put in simple terms, machine learning facilitates complex problem solving by creating accurate predictions without the need for complex computer programming. Machine Learning’s strategic role in the modern organization In enterprise business...

If recent reports are to be believed, there will be a need for an additional 346,000 data scientists in Europe by 2020. This clearly shows the skills gap in the UK in the field.   The demand for data scientists and analysts is increasing, but there is not enough talent in the market. The Annual activity report 2015 of the European Commission highlights the problem more precisely. At that time, 77% of data analyst jobs remained unfilled, and it was predicted that the problem would become worse with a 160% increase in demand by 2020. The reason behind this yawning talent gap is clear – demand has surpassed supply and there is a lack of corporate training in data analytics .   There has been an exponential growth of data sources as well as of organizations’ hunger to utilize this data and make the most of the data collected from the disparate sources. A recent study conducted by the International Data Corporation predicts that the 'digital universe' will reach 40 zettabyte...