Join us as we explore organizational data, one of the most critical assets in modern business. It is estimated that organizations collect over 2.5 quintillion bytes every day—yet many struggle to translate this data into actionable insights. In fact, studies show 60% to 73% of enterprise data goes unused for analytics.
Why do organizations face so many obstacles to realizing value from their data? Some common themes include:
- It’s extremely difficult to operate and govern hundreds, if not thousands, of databases.
- Data and systems are generally disparate, siloed, and lack interoperability.
- Disparate data systems or a lack of data estate strategy can frequently lead to poor-quality data that’s hard to extract value from.
- Platforms are technical and require advanced analytics skills.
- It can be next to impossible to gain BI or AI adoption across the organization, in turn making it hard to streamline data sharing and accelerate insight discovery across teams and LOBs.
- Costly integration tax and ongoing maintenance can be cumbersome.
- Large amounts of data come with greater security and governance risks, especially as it gets shared more widely across an organization, and there is a need to deliver on the promise of analytics, but resources are limited.
Join our experts as they discuss how organizations can successfully build a strong data analytics foundation and what should be considered, such as:
- Data infrastructure (data lakes, warehouses, pipelines).
- Data tools and platforms (BI tools, machine learning, data visualization).
- Data processes (data governance, quality control, and security).
- People and skills (data analysts, engineers, and data-literate staff).
