Research

Abstract:

Data is the fuel of the business, creating new value and offering greater insights. A data lake environment plays a foundational role in helping extract value from data, and artificial intelligence initiatives are no exception. As the demand for faster access to data increases, massive scalability is no longer enough for modern data lake environments, so these environments increasingly leverage flash-level performance as well.

Abstract:

The recent and massive uptick in AI investments has been driven by the fact that these projects are, by and large, successful. This success often fuels an increase in the number of AI objectives, which places greater demands on IT and the underlying infrastructure. To ensure continued success with AI, the right infrastructure must be in place to consolidate data storage and accelerate its usage across the entire data pipeline.

Abstract:

In early 2021, the Enterprise Strategy Group (ESG) and the Information Systems Security Association (ISSA) conducted the fifth annual research project focused on the lives and experiences of cybersecurity professionals. This year’s report is based on data from a global survey of 489 cybersecurity professionals.

The cybersecurity skills gap discussion has been going on for over 10 years, and the data gathered for this project confirms that there has been no significant progress toward a solution to this problem during the five years it has been closely researched. The skills crisis has impacted over half (57%) of organizations. The top ramifications of the skills shortage include an increasing workload (62%), unfilled open job requisitions (38%), and high burnout among staff (38%). Further, 95% of respondents state the cybersecurity skills shortage and its associated impacts have not improved over the past few years while 44% say it has only gotten worse.

To download a complimentary copy of this report, please visit https://www.esg-global.com/esg-issa-research-report-2021.

Abstract:

Data teams and developers continue to serve as the lynchpin to businesses, overcoming shortcomings associated with more rapidly and reliably gaining insight from growing data sets. With improving data analytics for real-time business intelligence (BI) and customer insight consistently ranking as one of the business priorities driving significant technology spending, how are organizations enabling more end-users to actually leverage data? Skills gaps, collaboration, and accessibility have created several barriers for democratizing analytics across organizations, and pressure is being placed on data and software teams to make business intelligence easier to leverage and consume. But with the dynamic nature of the business being what it is today and the constant shifting of priorities, timeliness of delivery and accessibility of simplified analytics are being scrutinized. Embedded analytics is increasingly becoming the answer.