Company experts share their insights into 2020 trends in Data Analytics, AI, Machine Learning, Deep Learning, Digital Transformation and more
MicroStrategy® Incorporated (Nasdaq: MSTR), a world reference in analytics software and enterprise mobility, has just released the 10 Enterprise Analytics Trends To Watch In 2020 report on best practices in evaluating, deploying and using analytics and business intelligence technologies.
In collaboration with leading analysts and influencers from Forrester, IDC, Constellation Research, Ventana Research and others, MicroStrategy highlights trends and their insights that range from artificial and mobile intelligence, to data explosion, data sources, plus a few factors including an anticipated shortage of data analytics talent.
"We are excited to present our annual report on the key trends in Enterprise Analytics to watch in 2020. We see a growing opportunity for decision makers to leverage the latest trends and advances in enterprise analytics, IA, ML, Deep Learning and more." explains Vijay Anand, vice president of product marketing at MicroStrategy. "By collaborating with some of the world's leading experts in the field, the report aims to foster a very fruitful discussion with leaders seeking disruptive technologies to leverage Data Analytics, drive greater efficiencies, achieve ROI and outperform the competition."
Check out the Top 10 nominated by MicroStrategy:
1. Deep Learning Offers a Competitive Advantage
"In 2020, the spotlight with regard to Deep Learning will be focused on the relationship between knowing and doing. It is no longer just a buzzword, the pragmatic advent of Deep Learning to predict and understand human behavior is a disruptive storm on how companies will employ intelligence against their competitors," points out Frank J. Bernhard, director of data and author of "SHAPE-Digital Strategy by Data and Analytics.
2. AutoML improves the ROI of data science initiatives
"Machine Learning is one of the fastest evolving technologies in recent years, and the demand for Machine Learning development has increased exponentially. This rapid growth has created a demand for ready-to-use models that can be applied easily and without expert knowledge ”, explains Marcus Borba, founder and principal consultant at Borba Consulting.
3. The semantic graph becomes fundamental to add value to the business
"The semantic chart will become the backbone supporting data and analytics in an ever-changing data landscape. Organizations that don't use a semantic chart are at risk of seeing ROI related to analytics drop due to increasing complexity and organizational costs results," says Roxane Edjlali, senior director of product management at MicroStrategy and a former analyst at Gartner.
4. Human vision becomes even more important as the volume of data increases
"As more and more people feel comfortable working with data, they must also become familiar with the ethnography of the data or with the study of the points to which it relates, the context in which it was collected, and the understanding that the given alone does not provide a complete picture of the situation," explains Chandana Gopal, Research Director, IDC.
5. The New Generation of Embeeded Analytics Speeds Up Time and Gaining Insights
"Concise analytics provided in the context of specific applications and interfaces speeds decision making. This style of embedding and curating concise, contextual analytics can take longer, and with advances including no-code and low-development methods code, we're seeing increasing adoption of the next generation of Embeeded Analytics," says Doug Henschen, VP and Principal Analyst, Constellation Research.
6. The need to combine data sources continues to grow
"We hope to see a continued focus on data diversity. Organizations rarely have a single, standardized Data and Analytics platform, and multiple tools are used to access the data. The need to combine these data sources will only continue to grow," says David Menninger, senior vice president and research director for Ventana Research.
7. Data-oriented skills become a requirement in companies
"Companies will need to focus their attention not only on recruiting people with strong analytical skills, but also on educating, qualifying and improving current employees, as the need for data-driven decision making only increases – and talent shortages too," said Hugh Owen, executive vice president of global education, MicroStrategy.
8. AI is real and ready
"In the coming year, more of these confident CDAOs and CIOs will ensure that data science teams have what they need to be effective, and so they can spend 70%, 80% or 90% of their time actually creating AI models to implement." indicates Srividya Sridharan, Mike Gualteri of Forrester.
9. Mobile Intelligence Evolves to 2020 and Beyond
"Half of organizations will re-evaluate their use of mobile devices and conclude that their technology does not adequately meet their employees' needs, leading them to look at a new generation of mobile apps that enable a better work experience and much more effective connectivity for the rest of the organization and to customers," says Mark Smith, CEO and Director of Research at Ventana Research.
10. The future of Experience Management is powered by AI
"As applications are decomposed by the business process for headless microservices, automation and intelligence will play an important role in creating personalization and efficiency at mass, and at scale. Smart Enterprise will bring context and Data Analytics to Boost your next actions," warns R" Ray "Wang, Founder and Principal Analyst, Constellation Research.
To read the full content of each thought leader, download the report, 10 Enterprise Analytics Trends To Watch In 2020.
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