Trend in Analytics Industry
As usage of words like ‘Analytics’, ‘IoT’, ‘Data Science’ in managerial meetings of companies is increasing day-by-day, expectations from Analytics teams and firms have increased manifold. With more sophisticated data collection techniques and systems emerging, companies are concentrating on focused and accurate analysis vis-à-vis profitability. The way data is being churned has also transformed significantly over the years. It is no more limited just to analysis of past data into graphs and charts but has gone further with machine learning and data science. It thus becomes important to know trends and future of this dynamic analytics domain to allocate companies’ resources accordingly:
Analytics - Art of Science!
Along with improvement in data collection techniques, we can soon see good amalgamation of art and science in analytics. Excellent visualizations, eased access, multi-platform optimizations are expected to take place in upcoming year!
More Machine Learning
Automation is the new buzzword. Why not automate Analytics when you have automated every other process in business! Machine learning is a data analysis method which automates analytical model building. Emphasis will be given in future to make it more accurate and feasible for implementation.
Rising number of data sources and touch points will bring in even more data on plate of analytics teams.
More Analytics Jobs. More Investments
World will need more ‘Scientists’, Data Scientists. As said previously, increased usage of analytics even by smaller companies will pull in more investments, jobs followed by increased number of startups specializing in analytics.
Undoubtedly, E-Commerce Analytics will be one of the most important trends in coming days. With advanced data-tracking tools and integration systems, E-commerce giants will use Analytics to outperform each other in the fierce race.
Internet of Things (IoT) is not as far as it seems now. IoT being majorly driven by Artificial Intelligence will require high level of decision making algorithms. This highlights the ever-increasing need of practice of analytics in IoT.
Amount of incoming data is growing and so will speed of data being processed. Amount of data being redundant per unit time will increase drastically. So faster processing and analysis systems will be future!
Privacy Concerns – With great powers comes great responsibility
?As data points will become open to all in a futuristic collaborative environment, at the same time it will become more vulnerable to privacy threats. It will thus be a challenge to harness all these features with care and build sustainable businesses.
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