Data Trends: Analytics, Governance, and More in 2026 | Coursera

在這個單身日致力於職業發展。 享受全年的 Coursera Plus，享受 40% 的折扣。
Familiarize yourself with past, present, and future data trends in this 2026 guide to the data industry.
Data trends cover changes in data analytics, big data, data privacy, data breaches, and data careers.
Some current big data trends include edge computing and non-database processing solutions.
Trends in data refer to patterns that demonstrate a general change in the data and tech landscape over the last several years.
Data science trends include the rise of generative AI, the emergence of roles such as chief data officer, and the growth of big data generated by mobile devices. Explore notable data trends over the previous year, and compare them to the forecast for data science, analytics, and privacy trends.
When you’re ready to further develop your data skills, consider enrolling in the IBM Data Analyst Professional Certificate. You’ll have the chance to learn about in-demand data and AI skills in as little as four months. Upon completion, you’ll earn a career certificate for your resume.
Here are a few of last year’s top trends in data, according to Gartner [1]:
AI risk management: The use of artificial intelligence (AI) in daily business processes has proliferated in recent years. While it has streamlined workflows and, in some cases, cut down on costs, it has also introduced security vulnerabilities and ethical conundrums. Data poisoning is an example of a cyber threat inherent to AI and machine learning (ML) technology. Adhering to regulations is key to any data management strategy, but AI ethics and responsibility go beyond that. Sustainable AI use must be coupled with governance to maintain trust, make informed decisions, and effectively measure value.
Data sharing: The concept behind this trend is for organizations to create “data as a product.” In short, this means applying product thinking to data sets by securing them, ensuring their discoverability, and strengthening their trustworthiness. Data sharing can enhance transparency and trust among stakeholders and consumers. It also improves connections among researchers, building efficiency by enabling the pooling of resources.
Conscious automation: In SolarWind’s 2026 global survey, 34 percent of IT professionals responded that their organization has somewhat adopted automation technology, while 16 percent reported their organization had completely adopted AI and automation [2]. However, keeping humans in the loop to make strategic decisions is key to a responsible automation initiative. A strong data literacy program should encourage a combination of advanced analytics with human decision-making at the helm.
Thoughtful AI integration and data literacy training were both highlighted at the Gartner Data and Analytics Summit in June 2025 and will remain core data trends until 2027 [3].
A trend in data is a pattern that indicates a general change in something over time. This article examines trends identified by various sources in the tech industry, including technological research and consulting firms like Gartner and enterprise-level companies like Amazon.
There’s no denying the buzz surrounding generative AI in 2025, particularly in the data science space. An Amazon Web Services (AWS) sponsored survey revealed that 87 percent of respondents are taking action to ensure their data strategy is capable of extracting value from generative AI [4]. Despite this, more than half of the respondents reported making no changes to their data yet. Data executives suggest that the economic value of generative AI has not yet been delivered and that implementation is still largely experimental. These insights align with the shift toward the AI trust, risk, and security management (AI TRiSM) framework in the IT space.
The evolution of executive roles is a notable data analytics trend for 2025. An MIT survey sponsored by Thoughtworks showed that 87 percent of data leaders and tech executives agreed that people in their organizations are confused about where to resolve data and tech-related issues or obtain relevant services [5]. The same survey revealed that 79 percent of C-suite decision-makers reported organizational hindrance due to a lack of collaboration with other tech leaders [5]. As time goes on, we might see a shift toward broader, overarching tech leadership positions rather than specific, specialized roles such as chief data and analytics officer.
Read more: 4 Data Analyst Career Paths: Your Guide to Leveling Up
The vast amounts of data generated today across various platforms like smart devices, mobile phones, and web applications can be challenging to collect and process, especially in real-time. These conditions lead to dark or unprocessed data and missed opportunities for gathering valuable insights. In response, edge computing is on the rise for processing data close to or on the originating device. The increasing prevalence of the Internet of Things (IoT) emphasizes the need for big data analytics solutions, and non-database sources can be key.
Hear more about big data in this lecture from Cloudera's Modern Big Data Analysis with SQL Specialization:
For two consecutive years, reports have identified data governance as the top activity on which chief data officers (CDOs) spend their time [6]. Strengthening governance procedures is among the top trends not only in data but also in cybersecurity and IT. This shift can partly be attributed to the need to work responsibly with emerging technologies like generative AI. However, governance is also critical for maintaining the quality and trustworthiness of data.
In April 2024, comprehensive privacy bills were passed in New Jersey, Kentucky, and New Hampshire. These actions came after a momentous 2023, when the number of states with comprehensive privacy laws jumped from five to 13. WilmerHale Privacy and Cybersecurity Law firm predicts this state-level trend will continue, projecting the following year to be active for privacy regulators