Data 2020:State of Big Data Study A global study of enterprise data challenges and solutions

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As data’s importance grows, so does its complexity. Enterprises are challenged to make informed business decisions

within a fragmented IT environment. SAP studied a wide variety of issues associated with enterprise data, illustrating

a data management landscape ripe with opportunity, yet challenging to manage across roles and departments.

Data Quality & HealthA modern data environment is siloed, complex and data quality is unclear.

However, enterprises are taking the necessary first steps to improve data discovery and governance.

Data Sources, Connectivity & IT FrameworksDue to rising data complexity, businesses are not as agile and data-driven as they need to be.They increasingly value the opportunity that analytics solutions provide to integrate silos and obtain valuable insights.

74%86%say there is much more they can do with their data,while 74% say their data landscape is so complexthat it limits agility

86%

Discovery

50%believe that data is inaccessible to a wide variety of business stakeholders, while 14% believe that data cannot be accessed at all

50%14%

Health

Most Important Technologies

would benefit from using a data integration solution

83%say their company’s data needs more than just a check up to make it healthy

79%

Location

of data is on premise, versus 26% in private or public clouds VS.37%

of companies incorporate data from applications outside the enterprise

68%

Enterprise Applications (ERP, CRM)

Email, Word Processing, Spreadsheets

DocumentManagement

Third-partyData Sources

Social Media Geospatial

72%

85%struggle with data from a variety of locations, and 72 percentsay that their data landscape is complex with the variety and number of data sources

85%72%

68% 59%

59%

54% 53% 32%

believe that their data is of very high quality

23%

37% 26%

Clean data daily Clean data a few times per week

Clean data a few times per month

Clean data once a month

Rarely clean data

25% 25% 24% 17% 7%

Operations Finance Sales and Marketing Human Resources Other Departments

85%

Internet of Things Machine Learning

81%

AI

81%

Analytics

96%

Most Important Data Sources

17%

Machine LearningInternet of Things

19%

AI

15%

Most Likely to Use Data Analytics Solutions

Key Data Stakeholders

Most Challenging Data Sources

Data LakesPublic/PrivateClouds

Enterprise Information Management Tools

Data VisualizationTools

Data MartsDataWarehouses

Hadoop

49% 44% 38%

38%

38% 31% 30% 26%

Skills, Capabilities & OwnershipThere is a need to address the high demand for jobs in data science

to prevent a potential job skills shortage.

Big Data has been coined the new gold, and companies believe that it’s time to make data scientists the new gold miners.

of companies currently have data scientists. 79 percent say that data scientists are important in making sure the company is successful, and 78 percent believe there will be a shortage of people with the right skills to successfully work with data

53%79% 78%

of companies say data scientists should focus on data inside the enterprise, versus 38 percent who say they should focuson data outside the enterprise

59%

24%

Sales and MarketingOperations Finance Human Resources

40% 21% 13%

13%61% 52% 49% 43%

75%believe that both IT and other departments should be the primary departments handling data analytics

When implementing data management systems, the most common recommendations are:

More oversight from IT

More technically qualified people

A more streamlined process for requesting and granting data permissions

Easier to use tools

Study conducted by Regina Corso Consulting, commissioned by SAP, August 2017. Respondents were enterprise IT decision-makers from the United States, Canada, Brazil, Germany, France, United Kingdom, Japan, China, Australia.

For more information on how SAP helps enterprises manage complex data,

visit www.sap.com/datahub

About the Study

VS.