As the amount of data continues to grow, so does the potential for advanced analytics to make sense of it all. In 2024, tremendous progress will be made in analytics, according to our merry band of prognosticators.
It’s hard to avoid the siren call of generative AI. But as the calendar flips over in two weeks, know that a successful GenAI strategy depends on data and analytics setting up the show, according to Forrester analysts.
“If generative AI is the star actor in ‘Business Technology: The Musical, 2024,’ data and analytics leaders are the stage managers,” the tech analysts write. “According to Forrester’s July 2023 Artificial Intelligence Pulse Survey, 89% of AI decision-makers say their organizations are expanding, experimenting, or exploring the use of GenAI. But before the star technology can deliver value for its audience of stakeholders and customers, data and analytics leaders must enable the people, processes, and platforms to set the stage for success.”
In 2024, English will replace SQL as the lingua-franca of business analysts, asserts Nima Negahban, the CEO and co-founder of Kinetica.
“We can anticipate a significant mainstream adoption of language-to-SQL technology, following successful efforts to address its accuracy, performance, and security concerns,” Negahban says. “Moreover, LLMs for language-to-SQL will move in-database to protect sensitive data when utilizing these LLMs, addressing one of the primary concerns surrounding data privacy and security. The maturation of language-to-SQL technology will open doors to a broader audience, democratizing access to data and database management tools, and furthering the integration of natural language processing into everyday data-related tasks.”
Not so fast, says Dave Stokes, a technology evangelist at database provider Percona, who says SQL is here to stay.
“SQL is proclaimed too old-fashioned every few years, and in 2024 proposals to use LLM AI tools to generate database queries will get a lot of attention,” Stokes says. “But one of the reasons SQL is the only programming language from the 1970s that still gets used so widely today is its power in querying data. You may not like the syntax. You may find its rules somewhat arbitrary. You may have gripes about learning such an old language. But for decades, SQL has proven itself again and again as the premier tool to manipulate data. It won’t be going out of fashion any time soon.”
Open data formats will deal a death blow to traditional data warehouses, says Justin Borgman, the co-founder and CEO of Starburst.
“While many anticipate the data lakehouse model supplanting warehouses, the true disruptors are open formats and data stacks,” Borgman writes. “They free companies from vendor lock-in, a constraint that affects both lakehouse and warehouse architectures.”
Seconding that motion is Kelly Kohlleffel, a senior global director of partner sales engineering at Fivetran.
“With the proliferation of LLMs and GenAI apps requiring structured, semi-structured, and now unstructured data, data lake workloads will become the ‘must have,’ do it right workload, over cloud data warehouses in 2024,” she writes.
The usual BI and data analytics workflow will be uprooted in 2024, thanks to AI and natural language processing, says Jeff Hollan, director of product management for Snowflake.
“Today, business intelligence analysts generally create and present canned reports,” Hollan says. “In the coming year, executives will expect to interact directly with data summarized in that overview report using natural language. This self-service will free up analysts to work on deeper questions, bringing their own expertise to what the organization really should be analyzing, and ultimately upleveling their role to solve some of the challenges AI can’t.”
In addition to executives, NLP-powered analytics will also power the next wave of customer self-service, says Vasu Sattenapalli, CEO of RightData.
“Analytics have been stuck in dashboards, which will no longer be the only way to consume business insights,” Sattenapalli says. “Voice and Generative AI will enter the analytics space where you can ask questions of your data verbally and get a response back in minutes, if not seconds. Imagine even pulling out your phone with an app specific to your organization’s data and being able to access a world of insights. It’s coming!”
Forrester analyst Michael Gualtieri has a theory that everybody wants to be treated like an A-list celebrity online. That dream will become reality in 2024 thanks to tech that makes hyper-personalized ecommerce experiences possible, says Naren Narendran, chief scientist at Aerospike.
“Rather than platforms serving content based on aggregate statistics or the behavior from a buyer’s journey in the past six months, for example, they’ll react based on a search from three hours ago–or even a click from two minutes ago,” Narendran says. “As ML systems are fed more and more data to boost application performance, we’ll see generalized statistical predictions funnel into hyper-personalized ones at the individual level for a more tailored user experience in retail and ecommerce.”
In the past, data was called the new oil. But in 2024, data you can actually trust will become the most critical asset in the world, according to Satyen Sangani, CEO and co-founder of Alation
“The critical role of trusted data in AI systems is becoming a cornerstone for the future of technology,” Sangani says. “Ensuring the information and data that come out of the AI system are trustworthy is just as critical. In a world that’s inching closer and closer to artificial general intelligence (AGI), knowing what to trust and who to trust will be critical to everything we learn and everything we think we know.”
This trusted data will be critical for AI systems to power the one in 10 operational tasks that Forrester predicts will occur, Sangani continues. That magnifies the importance of trust in data.
“The result is that AI governance is going to gain importance quickly,” he says. “It involves more than just managing data; it’s about understanding the entire lifecycle of information and models. The analogy of data as the new oil now seems insufficient in the era of generative AI and the challenges hallucinations bring. Merely amassing and analyzing large data sets is no longer adequate in today’s business environment.”
Another big believer in big data governance driving analytics success is Chetna Mahajan, the chief digital and information officer at Amplitude.
“In 2024, organizations will place a paramount focus on allocating resources towards enhancing data management and governance,” Mahajan writes. “This strategic emphasis aims to construct robust data repositories that serve as the fundamental basis for empowering data science, AI, and ML engines to furnish actionable insights. The absence of effective governance will lead to a lack of confidence within teams regarding their data, consequently impacting their decision-making capabilities.”
If the developing El Nino is as strong as some have suggested and results in adverse weather events, then 2024 could become a big year for geospatial analytics, according to Sean Donegan, the president and CEO of Satelytics.
“In 2024, extreme weather conditions, including hurricanes, floods, and drought due to El Niño and other climate/weather phenomena, will continue to threaten the infrastructure of utility companies, including power lines, poles, and more,” Donegan writes. “Geospatial analytics, utilizing high-resolution satellite imagery and AI algorithms, can pinpoint exactly where there are issues, such as trees encroaching on power lines, wildfire impacts, and any other damage to infrastructure. This capability allows a utility company to find the problem promptly and fix it before it worsens.”
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Author: Alex Woodie