Working with large volumes of data requires effective data management practices and tools, and two of the frequently used processes are data ingestion and ETL. Given the similarities between these two processes, non-technical people seek to understand what makes them different, often using search queries like “data ingestion vs ETL”.

We tested a product-led go-to-market motion last year. Here are the exciting results and learnings.

New legislation affirms the governance and security responsibilities of all organizations doing business in the EU.

Organizations are building data lakes and bringing data together from many systems in raw format into these data lakes, hoping to process and extract differentiated value out of this data. However, if you’re trying to get value out of operational data, whether on prem or in the cloud, there are inherent risks and costs associated with moving data from one environment to another.

The rise of AI-powered features in today’s analytics solutions has increasingly displaced our reliance on dashboards by making it easier for business people to analyze their data. With this rising paradigm shift, a new label has emerged: The augmented consumer. On a surface-level, the word ‘augmented’ may conjure up a variety of different interpretations. AI-based dashboard assistants? Natural language-led reporting?

What is kpi in business? A CFO Key Performance Indicator (KPI) or metric is a quantifiable high level measure of financial performance. These KPIs can be considered a specific subset of financial KPIs, used to help a CFO make informed decisions that steer their company in the right direction. These performance metrics can also be used to measure a company’s financial performance relative to competitors in the same industry.

A data catalog is a central inventory of organizational data. It provides a comprehensive view of all data assets in an organization, including databases, tables, files, and data sources. Efficiently managing large amounts of information is crucial for companies to stay competitive. This practice is especially applicable to large organizations with scattered data.