Data Lake Formation With Azure Cloud Platform Powerpoint Presentation Slides

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.