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Analytics

How to Improve Your CRM Data Management Based on Insights From 140+ Companies

At Databox, we’re firm advocates for improving your business through data. But just having that data isn’t enough – you need to manage it well for it to serve you. Customer relationship management (CRM) software excels at capturing the data you need for your marketing and sales operations. But that data needs regular upkeep and careful analysis for you to use it effectively. If you don’t feel like you’re on top of your CRM data management, you aren’t alone.

Databricks Data Lakehouse Versus a Data Warehouse: What's the Difference?

Businesses today rely heavily on data to inform decisions, predict trends, and optimize operations. However, more data volume and complexity has led to growing pressure to find scalable, cost-effective solutions for data storage while staying within IT budgets. Companies want to handle both structured and unstructured data efficiently, while supporting advanced data analysis and machine learning use cases.

New research from Confluent sees IT leaders share their biggest AI implementation challenges

12th September 2024 - Skills shortages are the #1 challenge facing IT leaders looking to implement artificial intelligence in 2024. That's according to research from Confluent, released ahead of this year's BigData LDN event. The research, which surveyed over 500 UK IT leaders, explores the top challenges facing IT departments when it comes to adopting and implementing AI.

Data Actionability: Boost Productivity with Unravel's New DataOps AI Agent

Right now, 88% of companies surveyed are turning to AI to improve bug-fixing effectiveness. Why? Troubleshooting modern data stacks is typically a toilsome and manual process. The good news – data teams that use DataOps practices and tools will be 10 times more productive (Gartner). With this in mind, Unravel introduces the new DataOps AI Agent. Learn how this new AI agent enables teams to go beyond observing data pipelines and errors to taking immediate action with purpose-built AI and automation.

How GenAI early adopters gain a competitive advantage in analytics

With generative AI, you have the opportunity to deliver a data strategy that helps business people answer their most pressing data questions—providing unprecedented value to your internal teams, partners, and customers. Hype around GenAI has overwhelmed people with too many use cases and too little focus on achievable value. That’s why we sponsored a first-of-its-kind survey with MIT SMR Connections, asking 1k global data and business leaders questions.