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A Smart Approach to Planning and Executing Data Lakes



What are the main data challenges faced by today's organizations?

Businesses today face significant challenges unifying, analyzing, and interpreting the vast amounts of data from various points they collect and turning them into insights and then effectively into actions. They are, in fact, searching for next-generation architectures that can attend to divergent data assets, accelerate data processing and analytics, and drive innovation with lower costs.

What kind of approach do businesses need for designing a data lake?

Businesses require different time frames and capabilities to grow their data lakes based on their strategic company objectives and technical qualifications at the beginning of the project. It is essential to underline that businesses should adopt an agile approach to their data lake design and rollout, observing various technologies and management approaches and testing and improving them before reaching optimal data storage and access processes. With the right approach, companies can bring analytics-driven insights to the market much faster than their competitors while significantly reducing the cost and complexity of their data architecture.

What are the fundamental questions businesses need to answer during data lake development?

Where is your data currently stored? | What is the total size of your data? | Where will you store your data? | How much do you need to transform your data? (EL/ELT/ETL) | How advanced are the current analytics tools? | Do you have traditional/modern development tools and methodologies? | Do you manage workloads dynamically? | How many concurrent data users do you generally require? | How fast do end users need to access the data?

Author: Gizem Terzi Türkoğlu

Published on: Sep 27, 2022