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Enthrall your audience with this Data Warehouse IT Powerpoint Powerpoint Presentation. 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 eighty nine 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 Warehouse (IT). State Your Company Name and begin.
Slide 2: This is an Agenda slide. State your agendas here.
Slide 3: This slide presents Table of Contents for Data Warehouse.
Slide 4: This is another slide continuing Table of Contents for Data Warehouse.
Slide 5: This is another slide continuing Table of Contents for Data Warehouse.
Slide 6: This slide shows Table of Content highlighting Current Scenario of the Business.
Slide 7: This slide depicts the current situation of our company by displaying the ratio of unstructured and structured data.
Slide 8: This slide presents gap in the organization by showing how big data is causing challenges.
Slide 9: This slide shows Table of Contents for Data Warehouse.
Slide 10: This slide displays need for a data warehouse in the organization, such as data quality, single point, etc.
Slide 11: This slide shows need for a data warehouse based on business users, storage for historical data, etc.
Slide 12: This slide depicts the data warehouse benefits for organizations such as time-saving, improved business intelligence, etc.
Slide 13: This slide presents Table of Contents for Data Warehouse.
Slide 14: This slide shows characteristics of data warehouses such as subject-oriented, integrated, time-variant, and non-volatile.
Slide 15: This slide represents the subject-oriented feature of data warehouse and various operational applications.
Slide 16: This slide depicts the integrated feature of the data warehouse and how different subjects are stored.
Slide 17: This slide shows time-variant feature of data warehouses and how they can store years-old information.
Slide 18: This slide illustrates the non-volatile feature of the data warehouse.
Slide 19: This slide shows Table of Contents for Data Warehouse.
Slide 20: This slide displays the basic architecture of a data warehouse and how information is processed and stored in this architecture.
Slide 21: This slide depicts the three-tier data warehouse architecture, including functions performed.
Slide 22: This slide describes a data warehouse architecture with a staging area.
Slide 23: This slide presents a data warehouse architecture with a staging area and data marts.
Slide 24: This slide shows data warehouse bus architecture and how it decides the flow of the data in the data warehouse.
Slide 25: This slide displays different views of data warehouses, such as top-down view, data source view, data warehouse view, etc.
Slide 26: This slide shows Table of Content for the presentation.
Slide 27: This slide depicts the various types of data warehouses, such as enterprise data warehouses, operational data stores, etc.
Slide 28: This slide presents the enterprise data warehouse (EDW) and its architecture, including the data source layer, staging area, etc.
Slide 29: This slide represents the types of enterprise data warehouses such as on-premises data warehouses, cloud-hosted data warehouses, etc.
Slide 30: This slide illustrates the operational data store and its architecture, including data sources such as unstructured and structured.
Slide 31: This slide depicts the data mart type of data warehouse, its architecture, and how a single department manages it.
Slide 32: This slide depicts the dependent data mart and how it can be established in two ways.
Slide 33: This slide presents the independent data mart and has no connection with the central data warehouse.
Slide 34: This slide depicts the hybrid data mart and how data is integrated into this type of data mart other than data warehouse.
Slide 35: This slide shows Table of Contents for Data Warehouse.
Slide 36: This slide depicts what a cloud data warehouse is and how it can store data from many data sources.
Slide 37: This slide shows the benefits of cloud data warehouses, such as cost reduction, data security, etc.
Slide 38: This slide represents what a modern data warehouse is and how it supports SQL, machine learning, etc.
Slide 39: This slide shows Table of Contents for Data Warehouse.
Slide 40: This slide displays the critical components of a data warehouse, such as load manager, warehouse manager, etc.
Slide 41: This slide represents the stages of data warehouse such as operational database, offline data warehouse, etc.
Slide 42: This slide represents the most prominent data warehouse solutions such as MarkLogic, Amazon RedShift, and Oracle.
Slide 43: This slide shows Table of Contents for Data Warehouse.
Slide 44: This slide depicts how the data warehouse works, including how operations such as extraction, transformation, etc.
Slide 45: This slide represents how data warehouses, databases, and data lakes work together.
Slide 46: This slide shows Table of Contents for Data Warehouse.
Slide 47: This slide represents the guidelines for data warehouse design, such as describing the business requirements, development of conceptual design, etc.
Slide 48: This slide presents the top-down design approach of the data warehouse, including its features such as time-variant, non-volatile, subject-oriented, etc.
Slide 49: This slide depicts the bottom-up design approach of the data warehouse and how data mart is built firstly in this approach.
Slide 50: This slide shows Table of Contents for Data Warehouse.
Slide 51: This slide depicts the business best practices to implement a data warehouse.
Slide 52: This slide describes the IT best practices for implementing a data warehouse, including tracking performance & security, maintaining data quality standards, etc.
Slide 53: This slide shows Checklist to Implement Data Warehouse in Company.
Slide 54: This slide represents the steps to implement a data warehouse in the organization, including enterprise strategies, phased delivery, etc.
Slide 55: This slide depicts the data warehouse implementation trends such as cloud data warehouse, data warehouse as a service, etc.
Slide 56: This slide represents the autonomous data warehouse with zero complexity deployment and how it will automate the routine.
Slide 57: This slide describes the budget for data warehouse implementation, including storage on the cloud, storage on-premise, etc.
Slide 58: This slide shows Table of Contents for Data Warehouse.
Slide 59: This slide depicts a comparison between database and data warehouse based on the design, type of information, etc.
Slide 60: This slide displays the comparison between data warehouse and operational database systems based on design, purpose, etc.
Slide 61: This slide depicts the comparison between data warehouse and data lake and how data is stored in the data warehouse.
Slide 62: This slide represents a comparison between data warehouse and data mart and how data marts can be designed for sole operational reasons.
Slide 63: This slide presents the comparison between data warehousing and business intelligence and how business intelligence helps to generate useful output from raw data.
Slide 64: This slide shows Table of Contents for Data Warehouse.
Slide 65: This slide represents the impacts of data warehouse implementation on the company.
Slide 66: This slide shows Table of Contents for Data Warehouse.
Slide 67: This slide represents the 30-60-90 days plan to implement a data warehouse in the company.
Slide 68: This slide presents Table of Contents for Data Warehouse.
Slide 69: This slide depicts the roadmap for data warehouse implementation in the company.
Slide 70: This slide displays Table of Contents for Data Warehouse.
Slide 71: This slide shows dashboard for data warehouse implementation in the organization.
Slide 72: This slide is titled as Additional Slides for moving forward.
Slide 73: This slide presents Table of Contents for Data Warehouse.
Slide 74: This slide represents what a data warehouse is, including its different data sources and the operations performed.
Slide 75: This slide displays the OLAP and OLTP in data warehousing and how OLAP tools are used for multifaceted data analysis.
Slide 76: This slide represents the extract transform and load tools of the data warehouse and how they perform their jobs.
Slide 77: This slide depicts the schemas in data warehouses such as star schema and snowflake schema.
Slide 78: This slide represents the massively parallel processing analytical database and how parallel processing is done.
Slide 79: This slide describes the applications of data warehouses in different industries such as banking, healthcare, government, etc.
Slide 80: This slide shows Icons Slide for Data Warehouse (IT).
Slide 81: This is a Comparison slide to state comparison between commodities, entities etc.
Slide 82: This is About Us slide to show company specifications etc.
Slide 83: This slide presents Post It Notes. Post your important notes here.
Slide 84: This slide shows Circular Diagram with additional textboxes.
Slide 85: This slide displays Puzzle with related icons and text.
Slide 86: This slide shows SWOT describing- Strength, Weakness, Opportunity, and Threat.
Slide 87: This slide shows Bar Graph with three products comparison.
Slide 88: This slide presents Venn diagram with text boxes.
Slide 89: This is a Thank You slide with address, contact numbers and email address.

FAQs

The purpose of the presentation is to discuss Data Warehousing, its benefits, architecture, types, and implementation strategies.

A data warehouse is a centralized repository of data that is used for reporting and analysis. Its features include being subject-oriented, integrated, time-variant, and non-volatile.

The different types of data warehouses include Enterprise Data Warehouses, Operational Data Stores, Data Marts, and Hybrid Data Marts.

A cloud data warehouse is a type of data warehouse that is hosted on the cloud. Its benefits include cost reduction, data security, and scalability.

The critical components of a data warehouse include Load Manager, Warehouse Manager, Query Manager, Metadata Manager, and Backup and Recovery Manager.

The guidelines for data warehouse design include describing business requirements, developing conceptual design, creating a physical design, and testing and maintaining the system.

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