Data is the new science. Big data holds the answers. Large open-access data sets offer unprecedented opportunities for scientific discovery. Scientists intending to make use of large composite data sets need to work closely with those
responsible for gathering the data. It is a new interdisciplinary field, in which teams of scientists use automated methods to collect, extract and analyze massive amounts of data to answer important questions heretofore not answerable.
Data science is a philosophy, a collection of methods and a suite of analytics that focuses on data storage, transport, and cleaning procedures in addition to visualization tools.
Many universities are developing departments of data analytics –especially those with academics medical centers and engineering schools to figure out how to train graduates to harness the power of all the data that is now available to
us-everyday-using powerful analytics. This new field is often unwieldy and faces many challenges. And the big question is how ready are we as a discipline and profession to take advantage of and contribute to big data science
The conference therefore addresses biggest challenges in Data Science and how we prepare our faculty, students and current scientists to be more aware of the precepts, methods and analytic tools in biomedical and health care fields.
The data science platform market size is estimated to grow from USD 19.58 Billion in 2016 to USD 101.37 Billion by 2021, at a Compound Annual Growth Rate (CAGR) of 38.9% during the forecast period. The base year considered for this report
is 2015 and the forecast period is 2016–2021. Data scientists apply advanced mathematics and statistics to address numerous business queries that delivers insights to management, thereby maximizing the return on assets and high Returns
on Investments (RoI). The Big Data market as measured by vendor revenue derived from sales of related hardware, software and services reached $18.6 billion in calendar year 2013. That represents a growth rate of 58% over the previous
year. Broken down by type, Big Data-related services revenue made up 40% of the total market, followed by hardware at 38% and software at 22%. Such a breakdown is due in part to the open source nature of much Big Data software and related
business models of Big Data vendors, as well as the need for professional services to help enterprises identify Big Data uses cases, architect solutions and maintain performance.
Broken down by type, Big Data-related services revenue made up 40% of the total market, followed by hardware at 38% and software at 22%. Such a breakdown is due in part to the open source nature of much Big Data software and related business
models of Big Data vendors, as well as the need for professional services to help enterprises identify Big Data uses cases, architect solutions and maintain performance.
The value of Big Data is in its potential to help practitioners make better strategic and tactical decisions, run more streamlined and efficient organizations, and deliver better products and services to customers. Vendors would be wise
to remember that it is such business value, not technology features per se, that will drive revenue in this market. In order to propel the Big Data market forward and entice early mainstream adopters, Big Data vendors must align not
just their marketing messages but product roadmaps to this reality. The development and forecast of the big data market is listed below.