According to a study from Dresner Advisory Services’ 2018 Big Data Analytics Market Study Big data adoption in enterprises ascended from 17 percent in 2015 to 59 percent in the year 2018, with growing CAGR of 36 percent. This is the 4th annual Big Data Analytics report the firm has performed, assessing end-user trends and intentions surrounding big data analytics, defined as systems that allow end-user access to and analysis of data contained and managed within the Hadoop ecosystem.
AWS S3, Hive, Spark SQL, and HDFS are the most popular big data access methods where AWS S3 is growing most rapidly in this year. Today, Apache Spark MLib and Tensorflow are the most-adopted big data analytics and Machine Learning technologies in enterprises. And Cloudera, Amazon EMR, Hortonworks, and MAP/R are the popular big data distributions by enterprises in the year 2018. Vice President and Research Director at Dresner Advisory Services, Jim Ericson stated that with the effort of four years of comprehensive big data analytics study, the firm perceived a strong upward trend in adoption and a corresponding drop in those without plans. This trend demonstrates a strong indication of mainstream adoption.
The study revealed some key insights that include telecoms, advertising, and insurance are the three industries who replied big data analytics is the most critical to their Business Intelligence initiatives. Healthcare, retail and wholesale industries rank big data analytics as indispensable to their ongoing Business Intelligence initiatives as well. 80 percent of all enterprises responded that big data is, at a minimum, imperative to their business intelligence initiatives.