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Finance leaders are facing the most turbulent trading conditions for more than a generation. The odds of recession are rising, US inflation has hit a 40-year peak, the “Great Resignation” has denied organisations the people they urgently need to go to market, stock markets have slumped, exchange rates are beyond volatile and, although abating, there is still the threat of a fresh round of Covid. Forecasting business performance has never been so challenging.

Data governance was an exclusive set of skills and tools based on old-school rules until a few years ago. Today, that's changed. While people who manage data still need tools, rules, and protocols to control and secure data use and sharing, three major trends have transformed the data ecosystem. First, the explosion of data from many nontraditional sources (personal devices, sensors, social data, etc.) provided businesses with massive and unprecedented information to dig for insight.

Corporations are generating unprecedented volumes of data, especially in industries such as telecom and financial services industries (FSI). Many organizations are hoping to leverage these massive amounts of data by investing heavily in big data solutions – solutions that they hope can meet business goals such as increasing customer satisfaction, uncovering alternative revenue streams, or improving operational efficiency.

Businesses aiming to deliver superior digital experiences, retain customers and innovate rapidly must seek ways to get value from data faster, and this is where real-time data warehousing helps.

Pub/Sub’s ingestion of data into BigQuery can be critical to making your latest business data immediately available for analysis. Until today, you had to create intermediate Dataflow jobs before your data could be ingested into BigQuery with the proper schema. While Dataflow pipelines (including ones built with Dataflow Templates) get the job done well, sometimes they can be more than what is needed for use cases that simply require raw data with no transformation to be exported to BigQuery.