Data Lake Formation With AWS Cloud Powerpoint Presentation Slides
This PowerPoint presentation gives a brief idea about a data lake, its essentials, foundational elements, architecture, need for data lake, and risks involved in data lake implementation. In this Data Lake Formation with AWS Cloud PowerPoint Presentation, we have covered the overview of the data lake by showcasing its main features, key concepts, primary components, and working. In addition, this Data Lake Architecture and The Future of Log Analytics PPT contains four data lake formations on different architectures such as AWS, Hadoop, and Azure, along with a cloud data lake. Moreover, this Data Lake Formation with AWS Cloud PPT contains the data lake implementation methods such as on-premise and cloud and the data lake implementation process. Lastly, this Data Lake Formation with Azure Cloud Platform deck comprises data lake vendors and tools, use cases and applications, and a comparison of the data lake with other storage systems. It incorporates slides showcasing a 30-60-90 days plan, a roadmap, and a dashboard for data lake reporting. Download our 100 percent editable and customizable template, which is also compatible with Google Slides.
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PowerPoint presentation slides
Enthrall your audience with this Data Lake Formation With AWS Cloud Powerpoint Presentation Slides. Increase your presentation threshold by deploying this well-crafted template. It acts as a great communication tool due to its well-researched content. It also contains stylized icons, graphics, visuals etc, which make it an immediate attention-grabber. Comprising seventy two slides, this complete deck is all you need to get noticed. All the slides and their content can be altered to suit your unique business setting. Not only that, other components and graphics can also be modified to add personal touches to this prefabricated set.
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Content of this Powerpoint Presentation
Slide 1: This slide introduces Data Lake Formation with AWS Cloud. State your company name and begin.
Slide 2: This slide states Agenda of the presentation.
Slide 3: This slide presents Table of Content for the presentation.
Slide 4: This is another slide continuing Table of Content for the presentation.
Slide 5: This slide highlights title for topics that are to be covered next in the template.
Slide 6: This slide represents the overview of data lake and how it stores machine learning analytics.
Slide 7: This slide showcases Main Features of Data Lake for Customer.
Slide 8: This slide shows Key Concepts of Data Lake Architecture.
Slide 9: This is another slide continuing Key Concepts of Data Lake Architecture.
Slide 10: This slide presents Primary Components of Data Lake Architecture.
Slide 11: This slide displays Essential Elements of Data Lake and Analytics Solution.
Slide 12: This slide represents the working of the data lakes, including how different types of data are stored.
Slide 13: This slide highlights title for topics that are to be covered next in the template.
Slide 14: This slide showcases Foundational Elements of Centralized Repository Data Lake.
Slide 15: This slide shows Process of Building Centralized Repository Data Lake.
Slide 16: This slide represents the building data lake team and their roles and responsibilities.
Slide 17: This slide highlights title for topics that are to be covered next in the template.
Slide 18: This slide displays why organizations should use data lakes based on their features.
Slide 19: This slide describes the value of a data lake including improved customer interactions, improved research and development innovation choices.
Slide 20: This slide depicts the purpose of the data lake in the business.
Slide 21: This slide showcases benefits of the data lake including low-cost scalability and flexibility.
Slide 22: This slide depicts the key pointers to help to understand organizations if they need to maintain a data lake for critical business information.
Slide 23: This slide highlights title for topics that are to be covered next in the template.
Slide 24: This slide presents Architecture of Centralized Repository Data Lake.
Slide 25: This slide displays Architecture Layers of Centralized Repository Data Lake.
Slide 26: This slide highlights title for topics that are to be covered next in the template.
Slide 27: This slide depicts the data lakes on AWS architecture through the data lake console.
Slide 28: This slide represents How to Implement Data Lake in Hadoop Architecture.
Slide 29: This slide describes the data lakes on Azure architecture by covering details of data gathering.
Slide 30: This slide highlights title for topics that are to be covered next in the template.
Slide 31: This slide describes the cloud-based data lake, how these data lakes can eliminate on-premise data lake challenges.
Slide 32: This slide depicts the cloud data lake challenges such as data security, data swamp, on-premise data warehouse, etc.
Slide 33: This slide represents the working of the cloud data lake.
Slide 34: This slide highlights title for topics that are to be covered next in the template.
Slide 35: This slide shows Risks Associated with Data Lake Usage.
Slide 36: This slide presents Critical Challenges Related to Data Lake.
Slide 37: This slide displays How Data Lakehouse Solves Data Lake Challenges.
Slide 38: This slide highlights title for topics that are to be covered next in the template.
Slide 39: This slide represents Strategies to Avoid the Data Swamp in Data Lake.
Slide 40: This slide depicts how to avoid a data swamp in a data lake.
Slide 41: This slide highlights title for topics that are to be covered next in the template.
Slide 42: This slide presents On-Premises Implementation of Data Lake.
Slide 43: This slide represents the deploying data lakes in the cloud and the percentage of believers in cloud computing.
Slide 44: This slide highlights title for topics that are to be covered next in the template.
Slide 45: This slide showcases Best Practices for Data Lake Implementation.
Slide 46: This slide depicts the stages of data lake implementation such as the collection of raw data, environment for data science, etc.
Slide 47: This slide showcases Overview of Maturity Stages of Data Lake.
Slide 48: This slide shows Introduction to Data Lake File Storage System.
Slide 49: This slide highlights title for topics that are to be covered next in the template.
Slide 50: This slide represents the data lake tools and providers, and tools are categorized based on storage, data format, etc.
Slide 51: This slide shows Prominent Vendors of Centralized Repository Data Lake.
Slide 52: This slide highlights title for topics that are to be covered next in the template.
Slide 53: This slide presents Use Cases of Centralized Repository Data Lake.
Slide 54: This slide displays Applications of Centralized Repository Data Lake.
Slide 55: This slide highlights title for topics that are to be covered next in the template.
Slide 56: This slide represents Difference Between Data Lake and Data Warehouse.
Slide 57: This slide showcases Comparison Between Data Warehouse, Data Lake and Data Lakehouse.
Slide 58: This is another slide continuing Data Lakes vs. Data Lakehouses vs. Data Warehouses.
Slide 59: This slide highlights title for topics that are to be covered next in the template.
Slide 60: This slide describes the 30-60-90 days plan for the data lake.
Slide 61: This slide highlights title for topics that are to be covered next in the template.
Slide 62: This slide presents Roadmap for Data Lake Implementation.
Slide 63: This slide highlights title for topics that are to be covered next in the template.
Slide 64: This slide displays Centralized Repository Data Lake Reporting Dashboard.
Slide 65: This slide contains all the icons used in this presentation.
Slide 66: This slide is titled as Additional Slides for moving forward.
Slide 67: This is an Idea Generation slide to state a new idea or highlight information, specifications etc.
Slide 68: This is a Financial slide. Show your finance related stuff here.
Slide 69: This is an Idea Generation slide with related icons and text.
Slide 70: This slide depicts Venn diagram with text boxes.
Slide 71: This is a Timeline slide. Show data related to time intervals here.
Slide 72: This is a Thank You slide with address, contact numbers and email address.
Data Lake Formation With AWS Cloud Powerpoint Presentation Slides with all 77 slides:
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FAQs
The purpose of a data lake in the business is to provide a centralized repository for storing all types of structured and unstructured data, enabling organizations to access and analyze this data quickly and easily.
The data lake team is responsible for the design, implementation, and maintenance of the data lake. Their roles include data analysts, data engineers, data architects, and business analysts.
The process of building a centralized repository data lake involves identifying the business objectives, selecting the right data sources, designing the architecture, implementing the system, and then testing and optimizing it.
The main features of a data lake include the ability to store both structured and unstructured data, as well as providing features such as data ingestion, exploration, storage, auditing, governance, security, quality, and lineage.
The primary components of data lake architecture include metadata, compute, format and storage. Each component is responsible for specific tasks within the architecture.
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