Companies are using more real-time analytics, because of the pressure to increase the speed and accuracy of business processes — particularly for digital business and the Internet of Things (IoT). Although data and analytics leaders intuitively understand the value of fast analytical insights, many are unsure how to achieve them.
In most ways, Internet of Things analytics are like any other analytics. However, the need to distribute some IoT analytics to edge sites, and to use some technologies not commonly employed elsewhere, requires business intelligence and analytics leaders to adopt new best practices and software.
Analytics-as-a-service offerings are based on broad categories and attract a range of players with different backgrounds. The urgency to transform into a digital business and to compete more effectively in the global market is forcing buyers to become more information-driven.
Data Sciences and analytics technology can reap huge benefits to both individuals and organizations – bringing personalized service, detection of fraud and abuse, efficient use of resources and prevention of failure or accident. So why are there questions being raised about the ethics of analytics, and its superset, Data Sciences?
Most organization do not take full advantage of the power of their data. They use it in only basic ways, such as creating reports and analyzing past trends. But what if they could do much more? What if they could find hidden patterns and ocnnections across all of their data? What if they could use those insights to anticipate future trends? What if they could take it yet a step further, creating thousands of possible scenarios and then identifying the ones most likely to achieve the organization’s specific goals?
A considerable amount of current conversation in the area of data science and analytics focuses on the virtues of solving all the challenges that organizations face when using this new paradigm in the business world. There is also a lot of discussion around the technology-related issues that impact achieving data science and analytics goals.
The world of data science and analytics is continuing to grow and adapt at an astronomical rate. Businesses are slowly able to piece together more information from different sources, meaning that they are able to make more sense of their data. Using data has become more and more important in creating new business opportunities and growth. Companies are still discovering the potential of utilizing data and the importance of monetizing that data in some form to benefit the business. Here’s what we can expect to see from the data science industry in 2017