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Data Lake Formation With Azure Cloud Platform Powerpoint Presentation Slides

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Deliver this complete deck to your team members and other collaborators. Encompassed with stylized slides presenting various concepts, this Data Lake Formation With Azure Cloud Platform Powerpoint Presentation Slides is the best tool you can utilize. Personalize its content and graphics to make it unique and thought-provoking. All the seventy five slides are editable and modifiable, so feel free to adjust them to your business setting. The font, color, and other components also come in an editable format making this PPT design the best choice for your next presentation. So, download now.

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Content of this Powerpoint Presentation

Slide 1: This slide displays title i.e. 'Data Lake Formation with Azure Cloud Platform' and your Company Name.
Slide 2: This slide presents agenda.
Slide 3: This slide exhibits table of contents.
Slide 4: This slide also shows table of contents.
Slide 5: This slide depicts title for seven topics that are to be covered next in the template.
Slide 6: This slide represents the overview of data lake is and how it stores machine learning, analytics, on-premise data movement, real-time data movement.
Slide 7: This slide represents the main features of data lakes, such as the ability to store structured and unstructured data.
Slide 8: This slide depicts the key concepts of data lake, including data ingestion, data exploration, data lineage, data storage, data auditing, etc.
Slide 9: This slide represents the key concepts of data lake such as data storage, data governance, data security, data quality, data lineage, etc.
Slide 10: This slide depicts the primary components of the data lake architecture, such as metadata, compute, format and storage, and the task of each component.
Slide 11: This slide describes the essential elements of data lake and analytics solution including data movement, analytics, machine learning, etc.
Slide 12: This slide represents the working of the data lakes, including how different types of data are stored at a centralized place, etc.
Slide 13: This slide depicts title for three topics that are to be covered next in the template.
Slide 14: This slide represents the data lake foundation elements such as data lake provisioning, data ingestion sources, landing zones, processing zone, etc.
Slide 15: This slide describes the process of building data lakes by defining how optimized data sets are created from raw data files.
Slide 16: This slide represents the building data lake team and their roles and responsibilities, including chief analytics officer, data analyst, etc.
Slide 17: This slide depicts title for five topics that are to be covered next in the template.
Slide 18: This slide represents why organizations should use data lakes based on their features including business agility, beneficial forecasts, etc.
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 such as beneficial for time-to-market analytics, IT-driven business process, etc.
Slide 21: This slide depicts the benefits of the data lake including low-cost scalability and flexibility, collection of multiple content sources, etc.
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 depicts title for two topics that are to be covered next in the template.
Slide 24: This slide represents the architecture of the data lake by defining its three major components such as sources, data processing layer, and targets.
Slide 25: This slide describes the architecture layers of the data lake such as ingestion, distillation, processing, etc.
Slide 26: This slide depicts title for three 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 and data lake command-line interface (CLI).
Slide 28: This slide represents the data lakes on Hadoop architecture by covering details of sources, ingestion tier, unified operations tier, etc.
Slide 29: This slide describes the data lakes on Azure architecture by covering details of data gathering, ingestion layer, etc.
Slide 30: This slide depicts title for three 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 and are scalable and cost-effective.
Slide 32: This slide depicts the cloud data lake challenges such as data security, data swamp, on-premise data warehouse, and data governance.
Slide 33: This slide represents the working of the cloud data lake and how different personnel of the company extract information from the centralized data repository.
Slide 34: This slide depicts title for three topics that are to be covered next in the template.
Slide 35: This slide depicts the risks of using data lake such as the higher risk involved in data lake construction, storage and computing expenses, etc.
Slide 36: This slide depicts the challenges of data lakes such as high cost, managed difficulty, long time-to-value, immature data security, etc.
Slide 37: This slide describes how data lakehouse solves data lake challenges through transactional storage layer, comparable data structures, etc.
Slide 38: This slide depicts title for two topics that are to be covered next in the template.
Slide 39: This slide depicts the strategies to avoid the data swamp in the data lake through data integrity, a comprehensive plan in place, etc.
Slide 40: This slide depicts how to avoid a data swamp in a data lake by defining the checklist of questions to consider.
Slide 41: This slide depicts title for two topics that are to be covered next in the template.
Slide 42: This slide depicts the on-premise data lake, how these are deployed and including its challenges such as space, setup, cost, etc.
Slide 43: This slide represents the deploying data lakes in the cloud and the percentage of believers in cloud computing, data warehousing and spark.
Slide 44: This slide depicts title for four topics that are to be covered next in the template.
Slide 45: This slide represents the best practices for the data lake implementation including support for native data types, management of data discovery, etc.
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 represents the maturity stages of the data lake, including handling & ingesting data at scale, building the analytical muscle, etc.
Slide 48: This slide represents the data lake file storage system based on big data’s five Vs such as volume, velocity, value, veracity and variety, etc.
Slide 49: This slide depicts title for two 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, compute, metadata and clients and libraries.
Slide 51: This slide represents the prominent data lake vendors such as AWS, Oracle, Google, Cloudera, Microsoft, and Snowflake and the services they provide.
Slide 52: This slide depicts title for two topics that are to be covered next in the template.
Slide 53: This slide depicts the use cases of data lakes such as data-in-place analytics, machine learning model training and archival and historical data storage.
Slide 54: This slide represents the application of data lakes in the media and entertainment industries, telecommunications industry, and financial services.
Slide 55: This slide depicts title for three topics that are to be covered next in the template.
Slide 56: This slide depicts the difference between a data lake and a data warehouse based on characteristics such as data, schema, price, etc.
Slide 57: This slide represents the comparison between data warehouse, data lake and data lakehouse based on the period and components of both.
Slide 58: This slide represents a comparison between data lakes, data lake houses, and data warehouses based on factors such as type of data, cost, etc.
Slide 59: This slide depicts title for one topic that is to be covered next in the template.
Slide 60: This slide describes the 30-60-90 days plan for the data lake by covering the tasks that will be performed at each interval.
Slide 61: This slide depicts title for one topic that is to be covered next in the template.
Slide 62: This slide represents the roadmap for the data lake implementation and how information should gradually store, clean-up and presented to the users.
Slide 63: This slide depicts title for one topic that is to be covered next in the template.
Slide 64: This slide represents the data lake reporting dashboard by covering the total number of users, total lake size, trusted zone size, etc.
Slide 65: This is the icons slide.
Slide 66: This slide presents title for additional slides.
Slide 67: This slide exhibits monthly line charts for different products. The charts are linked to Excel.
Slide 68: This slide exhibits quarterly bar charts for different products. The charts are linked to Excel.
Slide 69: This slide depicts posts for past experiences of clients.
Slide 70: This slide highlights comparison of products based on selects.
Slide 71: This slide displays puzzle.
Slide 72: This slide showcases financials.
Slide 73: This slide presents linear process.
Slide 74: This slide displays Venn.
Slide 75: This is thank you slide & contains contact details of company like office address, phone no., etc.

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