What Do Businesses Really Think About Data Analytics, Algorithms, and Machine Learning?

Companies expect big things from predictive analytics and machine learning.

In March 2018, Dell EMC surveyed 315 IT executives, in primarily mid-size and enterprise organizations across a wide range of industries, to investigate various issues around the current and future use of use of data analytics, predictive analytics, and machine learning. Findings reveal insights into:

General satisfaction with data analytics activities
Interest in automation for predictive analytics
Key benefits and deterrents associated with the use of machine learning
While more than a third of respondents say their organizations use big data/analytics (46%), predictive analytics (39%), algorithms (36%), and automated action triggered by algorithms (38%), the majority of companies have yet to embrace these technologies. It’s not that they’re not thinking about it, however. A full 28%-30% of respondents report that their organizations are either testing or considering each activity.

Satisfaction—Virtually Guaranteed

Most respondents who say their organizations use any or all of the four data-related technologies surveyed also express general satisfaction with them (see Figure 1). Only a small percentage of respondents, between 4% and 7% for each activity, say that they’re “not very” or “not at all” satisfied with the technologies.

Optimism Abounds about Predictive Analytics and Machine Learning

Many respondents expect to experience greater satisfaction with data-related technologies as predictive analytics and machine learning mature.

A clear majority (68%) of respondents who currently leverage data analytics, for example, believe that automation in predictive analytics will be a key differentiator for companies in terms of staying competitive. In fact, the majority of respondents whose companies currently use data analytics are also leveraging automated predictive analytics (76%) for important activities such as the detection of security breaches/threats (41%), followed by customer service (35%) and sales/revenue forecasting (35%) (see Figure 2).

Similarly, a majority (55%) of respondents who currently use data analytics believe machine learning can dramatically enhance those activities, and an additional third think that machine learning could “possibly” enhance their use of data analytics. According to the survey, the primary benefits of machine learning include the ability to:

Automate repetitive processes and tasks (72%)
Innovate faster and find new market opportunities (67%)
Improve customer engagement (63%)
Increase revenue (56%)
Only 18% of those using some form of data analytics are currently leveraging machine learning, however. While 55% are either considering implementing machine learning or researching it, several deterrents—primarily a lack of skills, talent, and understanding (47%) and a lack of budget for implementation (44%)—are holding them back (see Figure 3).

Enhance Your Data Analytics with Dell EMC Ready Bundles

Dell is committed to helping companies work with data for competitive advantage, with preconfigured solutions that accelerate adoption and mitigate risk. Take your data analytics to the next level with a Dell EMC Ready Bundle for Cloudera Hadoop (link to https://www.dellemc.com/en-us/solutions/data-analytics/hadoop/index.htm) or Dell EMC Ready Bundles for AI, Machine and Deep Learning. (link to https://www.dellemc.com/en-us/solutions/data-analytics/machine-learning/index.htm) For more information, contact your Dell EMC representative at 1-866-438-3622 and see a demo in our Dell EMC HPC & AI Innovation Lab, (link to http://i.dell.com/sites/doccontent/shared-content/data-sheets/en/Documents/dell-emc-hpc-lab-br-101_web.pdf) which is at the cutting edge of machine learning, testing new technologies, and tuning algorithms and applications to keep pace with the constantly evolving landsc

 

 

 

 

 

 

 

 

 

 

 

https://www.cio.com/article/3268170/analytics/what-do-businesses-really-think-about-data-analytics-algorithms-and-machine-learning.html



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