Explore the evolution of big data, cloud computing, distributed architectures, NoSQL databases, real-time processing, advanced analytics, ML, AI, and the 8 necessary steps for data management in this chapter.

Understand the need for smaller and accountable maintenance teams, re-imagining ownership and accessibility, simplified workflows and better developer experience with easier, faster, and more efficient data integration.

Encounter the challenges of finding the best data tool, importance of understanding data infra basics, dilemma of pricing v/s ROI, management complexities with multiple data tools, different data needs & importance of resilient data pipelines.

Navigate through the evolution of primitive data stacks (TDS and MDS) & highlights the defining factors of a Data-First stack. It also explores briefly introduces the concept of a Data Products & its importance in driving business objectives.

Dive deep into data processes focusing on activating metadata, refining data ingestion, smoothing data integration, optimizing the use of storage, and simplifying data transformation.

Engage with rich discussions on defining data ontology, speeding up easy & effective analytics, ensuring data security, standardizing observability & establishing data governance