CyberClick Data and Analytics 2023

• Digital Transformation
• Business Intelligence
• Cloud Technology
• Data as a Service (DaaS)
• Technology and Wellness
• Driverless Vehicles
• Big Data to Aid Climate Change Research
• Real-time Analytics Gain Traction Post-Pandemic
• More Natural Language Processing (NLP)
• Automation of Big Data Analysis
• Augmented Analytics
• Security Analysis With Big Data
• Robotic Process Automation (RPA)
• Artificial Intelligence as a Service (AI as a service or AIaaS)
• Predictive Analytics
• Migration to the Cloud

TechTarget Data Analytics Trends

• Artificial Intelligence
• Data Democratization
• Edge Computing
• Augmented Analytics
• Data Fabric
• Data-as-a-Service
• NLP (Natural Language Processing)
• Data Analytics Automation
• Data Governance
• Cloud-based Self-Service Data Analytics

Zawya Business Intelligence Trends

• Automation
• Augmented Analytics
• Predictive Intelligence
• NLP-based features for data democratisation
• AI-powered Intelligence
• Conversational Intelligence

The ECM Big Data Trends

• The rise of machine learning
• The need for better security
• Extended adoption of predictive analytics
• More cloud adoption
• More advanced big data tools
• Data lakes
• More data sources (IoT, smart devices)
• Data Fabric
• Data quality
• Flexible and customizable dashboard
• More restricted data governance

Spiceworks Data Trends

• Infuse Data Ethics Into Business To Protect Customer Privacy
• Boost Your Spending To Protect the Integrity of Big Data
• Improve Big Data Quality With AI & ML Workflows
• Emphasize on Regulations With a Focus on Responsible Data
• Tap Into AI/ML Tools That Enable Easy Processing of Data
• Propel Big Data Analytics With Microservice Architecture
• Go Beyond Tech and Address People-Based Aspects of Data Management
• Invest in Data Lakehouses To Enable Real-Time Reporting
• Leverage Vision AI To Create Insights From Video Data
• Build Quality Into Your Data Stream and Operations

Data Science Trends 2022

• Augmented Data Management
• Hybrid Forms of Automation
• Scalable AI
• Augmented Consumer Interfaces
• AI-As-a-Service Platforms
• The Democratization of AI
• Improved Data Regulation By Design
• Top Programing Language of Data Science is Still Python
• Cloud Computing with Exponential AI
• The Analytics Revolution
• The Impact of Natural Language Processing in the Future of Data Science

MuleSoft Digital Transformation Trends 2022

• The future of work will be built on connected, hybrid experiences
• The composable business matures
• The rise of the business technologist
• Hyperautomation unlocks digital value
• Security‑by‑default is a must‑have
• The rise of hybrid, distributed ecosystems adds complexity
• A single source of truth becomes key to the data‑driven business

InsideBigData Data Science Trends 2022

• Intersecting Supervised and Unsupervised Learning
• Training Data Complexities
• Annotating Data
• Structuring the Unstructured

Sigma Top Data Analytics Trends 2022

• AI will continue to improve, but humans will remain crucial
• Business intelligence adoption will grow in Technology, Business Services, Consumer Services, and Manufacturing
• Predictive analytics is on the rise
• Cloud-native analytics solutions will be necessary
• Self-service analytics will become even more critical to business intelligence

Bernard Marr’s Data Science Trends 2022

• Small Data and TinyML
• Data-driven Customer Experience
• Deepfakes, generative AI, and synthetic data
• Convergence
• AutoML

BearingPoint Technology Trends 2022

• Responsible AI
• Cloud at the edge
• Cybersecurity mesh
• Embedded data and analytics
• Connected sensors and machines

Dentsu Shopper DNA 2030

• UNIVERSAL ACTIVISM
• Shopping by values
• Regenerative retail
• Circular retail
• The data dilemma
• BIGGER BOLDER BRANDS
• The rise of titan brands
• Democratisation of retail
• Brand-engineered serendipity
• SYNTHETIC SOCIETY
• Robotic retail
• Customised reality
• Media as stores
• Playful purchasing
• THE HUMAN DIVIDEND
• Humain is premium
• Community commerce
• The stakeholder customer