The "digital business" has become the buzzword for what companies need to do after this decade is over. Despite its popularity, its definition is often unclear. At its technical core, it is about a shift in the way business data is sourced, from mainly from internal business processes to (largely) external data from the real world. Let me explain...
Already in the last millennium, the data that companies needed to operate was well structured, (reasonably) well managed and came almost exclusively from their bangladesh telegram screening own business units. This was process-driven data: the legally binding foundation of the company [1] . Relational databases - highly structured, carefully managed but resistant to change - dominated the data world. Data warehousing was the decisive factor for decision-making.
However, in the last decade, the data landscape has changed completely. Complexity and data volume are not only increasing due to the automation of processes and the demand for more agility. Social media, click streams and the Internet of Things have created huge amounts of raw and little pre-processed data: externally sourced, poorly structured, weakly regulated and with a changing structure over time. The focus of today's digital companies is on insights from this human-generated information and machine-generated data.
Relational databases fell out of favor and were replaced by NoSQL data stores of various forms. Data flowed into "data lakes" and threatened to wash away the dusty, old "data warehouses". But that didn't happen. Managing the (data) foundation of a company, using process-mediated data, is still mandatory.