Data Lake Formation With Hadoop Cluster 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 Hadoop Cluster 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.
-
- Google Slides is a new FREE Presentation software from Google.
- All our content is 100% compatible with Google Slides.
- Just download our designs, and upload them to Google Slides and they will work automatically.
- Amaze your audience with SlideTeam and Google Slides.
-
Want Changes to This PPT Slide? Check out our Presentation Design Services
-
- WideScreen Aspect ratio is becoming a very popular format. When you download this product, the downloaded ZIP will contain this product in both standard and widescreen format.
-
- Some older products that we have may only be in standard format, but they can easily be converted to widescreen.
- To do this, please open the SlideTeam product in Powerpoint, and go to
- Design ( On the top bar) -> Page Setup -> and select "On-screen Show (16:9)” in the drop down for "Slides Sized for".
- The slide or theme will change to widescreen, and all graphics will adjust automatically. You can similarly convert our content to any other desired screen aspect ratio.
Compatible With Google Slides
Get This In WideScreen
You must be logged in to download this presentation.
Do you want to remove this product from your favourites?
PowerPoint presentation slides
Enthrall your audience with this Data Lake Formation With Hadoop Cluster 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 five 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.
People who downloaded this PowerPoint presentation also viewed the following :
Content of this Powerpoint Presentation
Slide 1: This slide introduces Data Lake Formation with Hadoop Cluster. 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 slide displays Column chart with two products comparison.
Slide 68: This is Our Target slide. State your targets here.
Slide 69: This slide describes Line chart with two products comparison.
Slide 70: This slide depicts Venn diagram with text boxes.
Slide 71: This slide presents Roadmap with additional textboxes.
Slide 72: This slide contains Puzzle with related icons and text.
Slide 73: This is a Timeline slide. Show data related to time intervals here.
Slide 74: This slide shows Post It Notes. Post your important notes here.
Slide 75: This is a Thank You slide with address, contact numbers and email address.
Data Lake Formation With Hadoop Cluster Powerpoint Presentation Slides with all 80 slides:
Use our Data Lake Formation With Hadoop Cluster Powerpoint Presentation Slides to effectively help you save your valuable time. They are readymade to fit into any presentation structure.
FAQs
A data lake is a centralized repository that allows organizations to store all their structured, semi-structured, and unstructured data in one place. It can store machine learning analytics by enabling machine learning algorithms to access large volumes of data, process it, and extract meaningful insights.
The primary components of data lake architecture are storage, processing, security, governance, and metadata management. Storage provides a centralized repository for all types of data; processing enables the extraction of insights from the data; security ensures the data is protected; governance ensures the data complies with legal requirements; and metadata management allows for easy management and discovery of data.
The benefits of using a data lake include improved customer interactions, improved research and development innovation choices, low-cost scalability and flexibility, improved data analysis, and data-driven decision-making.
Data lakes store structured, semi-structured, and unstructured data in one place, while data warehouses only store structured data. Data lakes have a schema-on-read architecture, which means data can be stored without a predefined schema, while data warehouses have a schema-on-write architecture, which requires a predefined schema. Data lakes are designed to handle large volumes of data, while data warehouses are optimized for high-performance analytics.
The primary components of data lake architecture include data ingestion, data storage, data processing, data security, and data governance.
-
SlideTeam is the best in the business. Their templates are engaging and customizable. You can rely on them.
-
I am glad to have come across Slideteam. I was searching for some unique presentations and templates for my business. There are a lot of alternatives available here.
