Foundry has just launched its 2022 Data and Analysis Survey. The study contains information on data-driven initiatives, investments, challenges, results and global business strategies.
For the study, Foundry (formerly IDG Communications) surveyed 872 IT decision makers in March and April 2022. Answers came from companies around the world in many different industries, including technology, manufacturing, financial services, professional services, healthcare. , government, education. and retail, an average company with 12,498 employees. This is Foundry’s sixth data and analysis study, the most recent before this study being the 2021 IDG Data and Analysis Study.
Companies are motivated to extract value from existing data
Foundry defines “data-driven initiatives” as projects undertaken to generate more value from existing data, and 34% of organizations surveyed report that they have implemented such initiatives, compared to 28% in the 202 study. with 92% reporting data projects already underway, compared to only 79% of SMEs.
The motivation for extracting value from existing data varies by business sector. Half of those surveyed seek to improve or automate internal business processes. Others aim to improve customer understanding and engagement by 46%, along with customer service and support by 43%. Another 43% are looking to automate IT operations, while 36% want to improve existing products. Improvements in IT security were also a motivating factor at 36%.
“Data and analytics tools continue to improve, and clear demand for these types of projects will continue to effectively advance these initiatives,” said Stacey Raap, Foundry’s Marketing and Research Manager. “These tools provide invaluable information to companies, enabling them to increase performance and growth. We will probably see data and analytics tools in all parts of the business as they continue to move forward. ”
Data initiatives come with challenges
Organizations face challenges with their data initiatives, and the major pain points found in the study include data quality at 41%, followed by data security and governance at 38%, data analysis at 31%, and data preparation / transformation at 29%. In addition to these technical constraints, companies also have difficulty in developing skills, as 44% of respondents called the lack of adequate data skills as a problem, and 41% acknowledged the need for training in data analysis for non-technical users. . organizations. There is also a need for specialists in data architecture, as 42% of respondents noted, mostly in business-level business. Data analytics solutions remain inaccessible to 41% of organizations who say their technologies can only be used by qualified teams with skills in data science, AI and machine learning. Only 21% say that their data solutions are available for use by all users, and 83% of respondents considered focusing on self-service tools to be a top priority.
In addition, some companies have budget and strategy constraints that interfere with the implementation of data projects, as reported by 16% of respondents. Twenty-one percent of organizations with more than 1,000 employees noted that pandemic initiatives, such as remote work activation, have outpaced data projects.
“Like any part of an organization’s growing technology stack, there are always challenges to overcome, and IT teams and end users need to be given the right resources to keep moving forward,” Raap said. “Organizations need to invest in alleviating the pain points associated with data-driven tools and providing employees with the resources they need to hone their skills.”
Expenditure on data technology to remain relevant
Despite the difficulties, many companies spend on various data analysis technologies to gain an advantage. Of those surveyed, 77% invest in data to stay competitive in the market. Foundry says that, on average, IT decision-makers will spend $ 12.3 million on data-driven initiatives over the next 12 months, and 55% expect their IT budget for data-driven initiatives to grow next year from 44% in 2021.
Half of the decision makers surveyed currently use business intelligence platforms, followed by 34% who intend to invest in a BI platform in the next 2 years. Relational databases are also popular with 47% of respondents, followed by 28% who have invested in data science and machine learning platforms. Data warehouses of cloud-based enterprises are also used to run analytical workloads in the cloud and have already been adopted by 28% of respondents.
The decision of which vendors to engage with is another factor, as different vendors have distinct strengths and capabilities. In making these decisions, 36% of organizations rated data reporting and visualization capabilities as the most vital criteria, followed by security and governance capabilities and integration into existing infrastructure, both at 31%. Other criteria included the need for self-service analysis for non-technical users at 26%, along with the need for a data integration and transformation pipeline, also reported at 26%.
Artificial intelligence and machine learning technologies are also on the radar of decision makers, with 54% saying they have implemented or plan to implement predictive analytics next year. “[Predictive analytics’] the use of historical data, statistical algorithms and machine learning techniques helps organizations to create the best evaluation, similar to a crystal ball, of what will happen in the future “, the study summary shows. Machine learning is also used to detect data anomalies in 31% of respondents, as well as for descriptive analysis for customer analysis and natural language processing for virtual agents / chatbots at 29% and 28%, respectively.
The summary of the study concludes by reiterating that although companies face challenges in implementing their data initiatives, the need to remain competitive in today’s post-pandemic market leads to increased investment in data analysis.
“IT makers are purchasing or looking for easy-to-use business intelligence tools, cloud-based enterprise data warehouses and AI / ML platforms that give them access to predictive analytics, anomaly detection, process automation and decision support,” said Foundry. .
To learn more, download the executive summary from this link.
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