Unlocking the Business Value of the Data Lake

During this webinar where we’ll discuss how nearly three-fifths of organizations have gained competitive advantage from their data lake initiatives. That includes unleashing the intelligence-generating potential of a data lake that enables ad hoc data discovery and analytics in an open and flexible manner.

Transcript

1. Unlocking the Business Value of the Data Lake Matt Aslett VP & Research Director @ventanaresearch In/ventanaresearch blog.ventanaresearch.com © 2022 Ventana Research How Open and Flexible Cloud Services Help Provide Value from Data Lakes
2. © 2022 Ventana Research Data Lake
3. The Business Imperative for Data Lakes • Nearly three-fifths (59%) of organizations have gained competitive advantage from their data lake initiatives. • Almost half (49%) cite improved customer experience, and lowered costs (45%). • Better communication and knowledge sharing and faster response to opportunities and threats are also potential benefits. © 2022 Ventana Research
4. Departmental Benefitting from Data Lakes • Data lakes do not need to address the entirety of an organization. • Many organizations start in a specific department to prove the technological and business value and promote the benefits to build momentum. • Marketing, customer service, sales and finance are departments that benefit from data lakes. © 2022 Ventana Research
5. Flexible Data structure Adaptable Multiple use-cases Technical Benefits of Data Lakes © 2022 Ventana Research Low cost Cloud storage
6. Accelerated Migration to Cloud • Cloud lowers the time taken to commission, configure and deploy data infrastructure and software. • Cloud facilitates experimentation and innovation and lowers the cost (per GB) of storing and processing large volumes of data. • Almost three-quarters (74%) of organizations currently use, or are planning to use, cloud for analytics and data workloads. © 2022 Ventana Research
7. © 2022 Ventana Research Through 2025, 7 in ten organizations will be using cloud object stores as the primary persistence store for analytic data platform workloads.
8. Data Lakes and Data Warehouses • Data lakes have not, by and large, displaced data warehouses, which continue to be deployed. • Early data lake projects lacked the structured data management and processing functionality established in data warehousing. • More than two-thirds (67%) of organizations employ both, with many feeding data between the two environments. © 2022 Ventana Research
9. © 2022 Ventana Research Through 2024, data warehouse, data lake and data streaming technologies will converge to create analytic data platforms enabling organizations to collect and analyze all types of operations-generated information.
10. Storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness and unleash the power-generating potential of water in a lake or reservoir. Analogy: Hydroelectric Power Station © 2022 Ventana Research
11. Hydroelectric power relies on a combination of turbines, generators, and transformers to convert the energy of the flowing water into electricity. The equivalent of those turbines, generators, and transformers is required to harness and unleash the intelligence-generating potential of data in a data lake. Analogy: Hydroelectric Power Station © 2022 Ventana Research
12. Table formats Updates and deletes Additional Functionality © 2022 Ventana Research SQL engines Query concurrency and performance Metadata Metadata management and self-service discovery File formats Columnar storage and schema
13. Hydroanalytic Approaches Multiple approaches to delivering hydroanalytic data platforms: • deploying a data warehouse on or alongside the data lake • integrating DW functionality into the data lake (data lakehouse) Both are available as pre-integrated cloud services or can be assembled from open-source software and cloud services. © 2022 Ventana Research
14. Open source Open formats Openness and Choice © 2022 Ventana Research Open cloud
15. Multiple Clouds and Hybrid-IT © 2022 Ventana Research • Modern IT architecture spans multiple cloud providers as well as on-premises data centers. • Almost one-half (49%) of organizations are using cloud computing for analytics and data, of which 42% are currently using more than one cloud provider.
16. By 2024, more than three -quarters of current data lake adopters will be investing in data lakehouse technologies to improve the business value generated from the accumulated data. © 2022 Ventana Research
17. Recommendation © 2022 Ventana Research Reevaluate data lake use-cases • The incorporation of structured data-processing functionality with data lakes provides a direct alternative to the data warehouse as use cases evolve and mature. • All organizations—but especially those with data lake investments that are failing to deliver on their potential—should consider the evolution of the data lake in the context of additional functionality. • Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences.
18. Engage and Learn More on Analytics and Data Twitter @ventanaresearch @maslettvr LinkedIn http://www.linkedin.com/company/ventana-research https://www.linkedin.com/in/matt-aslett/ My Analyst Perspectives https://mattaslett.ventanaresearch.com/ Participate in Analytics and Big Data Research https://www.ventanaresearch.com/benchmark/big_data/big-data-for-business/survey https://www.ventanaresearch.com/benchmark/analytics/analytics_and_data/survey Learn More about Data and Analytics https://www.ventanaresearch.com/data https://www.ventanaresearch.com/analytics © 2022 Ventana Research
19. Unlocking the Business Value of the Data Lake Matt Aslett VP & Research Director @ventanaresearch In/ventanaresearch blog.ventanaresearch.com © 2022 Ventana Research How Open and Flexible Cloud Services Help Provide Value from Data Lakes