Analytics Remains Top Data Tech, Survey Says
Artificial intelligence is all the rage, but as companies continue to struggle with data complexity characterized by a variety and number of data sources, analytics remains the most important technology for squeezing value from far-flung data.
Analytics was cited by an overwhelming majority (96 percent) of respondents to a recent poll sponsored by SAP when asked to name the most important technology for a data-driven enterprise. AI and machine learning were cited by 81 percent, while 85 percent picked the Internet of Things.
IoT was ranked as the most important data source, followed by machine learning and AI, in that order.
Issues related to data complexity and the growing requirements for data management stem in part from the shift to data in the cloud. Nearly half of respondents to the SAP (NYSE: SAP) survey identified public and private clouds as the “most challenging data sources” followed by data warehouses, management and data visualization tools and data lakes. Hadoop databases were seen as least challenging, cited by only 26 percent of those polled.
In an attempt to reduce data complexity, 37 percent said data is stored on premises while 26 percent rely on private or public cloud storage. While enterprise data infrastructure remains siloed, adding to complexity, “enterprises are taking the necessary first steps to improve data discovery and governance,” the survey notes.
With analytics remaining a key technology for most businesses, the SAP survey echoes the need for more data scientists. Even as tools emerge designed to make data more accessible across organizations, the study found that 79 percent believe data scientists remain important, and an equal number worry about a data 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,” survey authors asserted.
As enterprises turn inward to squeeze value from the growing number of data sources, a majority of survey respondents said data scientists should focus on “data inside the enterprise” while only 38 percent said their focus should be on external data.
Moreover, IT operations are seen as the mostly likely enterprise user of data analytics, thereby making them the “key data stakeholders,” SAP reported.
SAP’s “State of Big Data” survey was conducted in August 2017.
The findings illustrate “a data management landscape ripe with opportunity,” the company further asserted. Among those opportunities are emerging data management approaches that go beyond relational database. Citing MongoDB’s (Nasdaq: MDB) stock offering on Thursday (Oct. 19), Datastax CEO Billy Bosworth noted in a statement: “There is a critical need for a new era of operational data management.”
Declining cloud storage and processing costs coupled with the growing data gravity of the cloud means companies are moving more operational and analytical workloads to the cloud.