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By 2022, what will be top 5 uses of data science at the Fortune 500, how much will they be spending on each, and how fast will each be growing?
Hello! Thank you for your question regarding the uses of data science among Fortune 500 companies.
The short version is that businesses are most interested in using big data analysis for (1) data warehouse optimization, (2) customer/social analysis, (3) predictive maintenance, (4) clickstream analytics, and (5) fraud protection. As seen in the top category, a move towards SVOT seems to be at the forefront of BDA spending.
BACKGROUND
Big data analytics (BDA) is the area of business concerned with the processes and methods used to extract knowledge and insights from data. Since 2015, BDA has gained tremendous popularity and was used by 53% of businesses that reported to Dresnor Advisory Services in the 2017 Big Data Analytics Market Study, up from 17% in 2015.
METHODOLOGY
To gain a better understanding of big data analytics (BDA) spending and usage among Fortune 500 corporations, a search was first performed to find statistics from industry reports. This search was fruitful in that it gave insights into the big data industry as a whole and the trends between data analytics spending and business size. To determine the top five uses of data science, two different metrics were determined and both are reported. One is a general approach, where spending is assumed to correlate with big data use. For example, the largest fractions of BDA expenditures are assumed to be the top usage areas.
The other list that is described is the top five uses as reported in the 2017 Big Data Analytics Market Study. I decided it was important to give this list as it highlights the specific areas businesses consider significant, whether their spending corroborates that notion or not. Given the difficulty in finding spending specific to Fortune 500 companies, industry-wide trends were assumed to be representative of F500 trends as well.
RESULTS
BDA spending is most popular among extremely large corporations, which can be assumed to overlap significantly with F500 organizations. Global BDA revenue is expected to continue growth at a CAGR of 11.7%, increasing from $130.1 billion in 2016 to $252.7 billion in 2022. This was calculated by holding the CAGR constant and using the formula FV = P(1+r)^Y. Specific data concerning the precise share of the market for each sector could not be found, but the relationships between spending and growth rate can be clearly distinguished given the information below:
In terms of spending, the top five uses of BDA in 2017 were:
(1) IT and business services
a. $75 billion+ in 2017
(2) Services-related spending
a. Five-year CAGR of 14.4%
(3) Software investments
a. $70 billion+ in 2020
b. Led by purchases of end-user query, reporting and analysis tools, and data warehouse management tools
(4) Non-relational analytical data store
a. CAGR of 38.6%
(5) Cognitive software platform
a. CAGR of 23.3%
From a qualitative standpoint, the top five areas of BDA usage are: (1) data warehouse optimization, (2) customer/social analysis, (3) predictive maintenance, (4) clickstream analytics, and (5) fraud protection. These usage categories were reported to Dresnor Advisory Services in the 2017 Big Data Analytics Market Study.
The industries that made the largest investments in big data in 2017 were banking, discrete manufacturing, process manufacturing, federal/central government, and professional services. These five industries are expected to spend $127.1 billion combined on BDA in 2022, up from $72.4 billion in 2017.
CONCLUSION
BDA is a rapidly-growing area that is becoming critical to large and F500 companies. The spending trends indicate that data science is seen as imperitave to business analytics, and a move towards a centralized database is evidenced by industry reports and anonymous reporting.