the State of Data and Analytics report - (c) SalesforceSalesforce and Tableau have published the State of Data and Analytics report. The report is based on a survey of more than 11,000 respondents from 18 countries across the world. Half were business leaders and half were Analytics/IT leaders. The high-level findings are not a surprise. Data fuels AI and a strong foundation of data is a key requirement. However, managing, securing and aligning data is still a challenge. Organisations must consider a range of strategies to ensure their data is fit for purpose, and these include data governance, internal culture and technology.

The report is twenty-eight pages long and divided into four sections:

  • Introduction: AI Puts Trusted Data in the Spotlight
  • Chapter 1: A Strong Data Foundation Fuels AI
  • Chapter 2: Data’s Full Potential Remains Elusive
  • Chapter 3: The Road to Data and AI Success Is Winding

There is also a supporting data visualisation tool powered by Tableau, which allows people to understand the survey results by filtering by country and industry. The report is also supported by a blog by Vandana Nayak, a Distinguished Architect at Salesforce, titled “Data Strategy in an AI-First World: Here’s Where to Start.”

Wendy Batchelder, Chief Data Officer of Salesforce
Wendy Batchelder, Chief Data Officer of Salesforce

The report itself contains the global responses with commentary and varied data visualisations that provide quick insights into the response. However, not all the visualisations are optimal, and more could have been done with colour.

Wendy Batchelder, Chief Data Officer of Salesforce, said, “The AI revolution is actually a data revolution, and a company’s AI strategy is only as strong as its data strategy, with trust at its core. Managing data is the most important action a business can take to successfully implement generative AI. To effectively manage data, leaders must use data governance strategically and invest in a strong culture now more than ever.” 

What is in the report


Reading the report, one is reminded of some of the key messages that Salesforce announced at Dreamforce around how it has built a comprehensive layer of compliance and security around the data it uses for its own AI and generative AI solutions. The research backs what it has already done and shows a way forwards.

Multiple surveys have indicated that generative AI is a game-changer, and 91% of business leaders say generative AI would benefit their organisation. However, to deploy AI, including generative AI successfully, leaders must have trust in their data. While 87% of analytics and IT Leaders (half the sample) say that advances in AI make data management a high priority, three countries were outliers. Only 79% felt the same in Japan and France, and only 76% did so in South Korea. The UK (89%) and the US (88%) were both slightly above average.

If data is the fuel that powers AI, it is no surprise that 92% of analytics and IT leaders agree the need for trustworthy data is higher than ever. 94% feel that they should get more out of their data. However, this is not happening, with the top two priorities, for IT leaders, being to improve data quality and strengthen security and compliance. Only then can they focus on the third priority, which is building AI capabilities.

A Strong Data Foundation Fuels AI

This chapter highlights some of the challenges organisations face when deploying a data strategy. Perhaps worryingly, the requirements for certain aspects seem low. Only 30% see ethical use guidelines as a requirement for successful generative AI use. 55% see accurate, complete and unified data as a requirement, and 54% believe they need enhanced security measures to avert new threats to the business.

The report looks at the link between data management and AI, with 86% of respondents agreeing that AI outputs are only as good as its data inputs. It looks at the benefits of AI and assesses the data maturity of organisations. Around 55%-60% of organisations believe they have data maturity around five factors: data quality, technology infrastructure, AI strategy, Tech talent, business stakeholder alignment and security/compliance. Those organisations with high-maturity are twice as likely than low-maturity respondents to have the high-quality data needed to use AI effectively.

Data’s Full Potential Remains Elusive

This chapter looks at the challenges facing IT and business leaders. 41% of line-of-business leaders say their data strategy has only partial or no alignment with business objectives. The challenges vary slightly between business leaders and the Analytics/IT leaders. However, all respondents agreed that security threats are top of mind. For business leaders, the next two data challenges are the volume of data and a lack of training. For IT leaders, it is the lack of data harmonisation and ensuring data quality. The inference, once IT leaders solve their challenges, it may get easier for business leaders.

The authors see data quality as a top priority. 57% of data and analytics leaders have complete confidence in their data’s accuracy, something seemingly at odds with the challenges noted. The line of business leaders is less confident. Only 42% of Sales and 40% of service leaders have the same level of confidence.

The report also looks at the issue of data overload, and the issue shows no sign of abating. With IoT devices rolling out, the potential for wearables and other innovations all feed the hunger for data. Business leaders are greedy for data but face a reality where they cannot consume it fast enough and arguably savour it.

The Road to Data and AI Success is Winding

The final chapter seeks to understand how organisations can find a path to success. The authors believe that a strong data culture will bring a series of benefits, including better productivity innovation and cost savings. However, barriers remain. To overcome these, many organisations are looking to invest 79% in data analysis and visualisation tools and 75% in training and development. The survey does not appear to indicate whether organisations are also looking to invest in data quality tools or security tools. Although the survey does indicate that IT leaders are aware of how they need to manage the volume of data with a variety of strategies.

If nothing else, the report highlights the complexity that IT leaders face with:

  • 47% using hybrid cloud or on-premises solutions
  • 44% are investing in better network infrastructure
  • 41% use multiple cloud providers
  • 40% employ decentralized or distributed data storage solutions

It is no wonder that IT leaders want to simplify data management by moving to the cloud. 43% have already moved, 28% are in the process of moving and 17% plan to do so in the future. 10% are considering it, and 2% have no plans to do so. The challenge of that 2% may be compliance; a qualitative element might have highlighted the reasons. Are they Luddites, or do they actually have valid reasons for not doing so?

The report concludes with an affirmation that 96% of business leaders say data and analytics improve decision-making and the top five priorities that Analytics and IT Leaders are considering.

Enterprise Times: What does this mean

This is a comprehensive report backed by a data visualisation that shows where peers within a geographical region or industry stand on the key issues. The analysis is solid, and the data backs the Salesforce approach to both data and AI. The authors provide high-level insights but do not dive into the specifics, for example, security, compliance or cloud architectures. The section around data maturity offers a lot but could have gone further.

What is also missing are comments and quotes from the respondents, to bring to life some of the statistics in the report. However, this is well worth a read, another solid, if high-level, report from Salesforce and Tableau.

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