Today, data is everywhere (internet, emails, sms, linkedin, twitter, facebook, online magazines, online newspapers, online journals, etc) and easily accessible and the result is ‘Big Data’ (data in a variety of forms, of different sizes and complexities). With many trillions of click stream records being generated every second, and aggregated to records with thousands of attributes, massive data and databases are being built. But how do we make sense of the massive data? There is a clear need and increasing demand for business analytics techniques to find patterns in the data and to present these in a simple way and at the same time display insights.
One of the challenges today is, in the past, business users relied on statisticians to analyze the data and to report the results. And, the results typically raised more questions and generally it took a long while, sometimes months, before business users could actually act on the results. Business users, while being domain knowledge experts in their particular areas, are not likely to be experts in statistics and business analytics.
Business users are also placing more demands on IT for more information in near real time. For organizations to better understand and improve the results of their business processes along one or more dimensions, organizations need data science teams which consist of experts in business analytics, domain knowledge and IT. Another key challenge for organizations is the transition of analytics onto mobile devices. Leading organizations have started to store data for mobile distribution.
With the growing variety in data, organization’s need to determine the types of data they want to analyze. It is also critical for organization’s to be able to leverage on both structured & unstructured data. The major challenge that organization’s face in today’s competitive environment is to identify which data is relevant and useful and then to transform the data into useful knowledge for business decisions.
Organizations need to have tools or roadmaps to put their analysis results and insights into use for actionable decision making. Organizations also need to share information throughout their enterprise, so that analytics can be used in a proactive way, to grow profits and streamline operations in the hope of gaining a competitive advantage over their competitors.
Carol, if you can sum it up in a couple of sentences, what is your take on data analysis for something as complex as discussions in social media? What is the general approach or stance nowadays?
Now a days most companies are moving more to Data Visualisation. They are making sense of their data visually, and using software that allows them to do more what-if scenarios, so that they can make decisions quickly, in almost real time.