Analytic Application Powerpoint Presentation Slides

Slide 1: This slide introduces Analytic Application. State Your Company Name and begin.
Slide 2: This is an Agenda slide. State your agendas here.
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 is another slide continuing Table of Content for the presentation.
Slide 6: This slide highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
Slide 65: This slide represents the impacts of data warehouse implementation on the company.
Slide 66: This slide highlights title for topics that are to be covered next in the template.
Slide 67: This slide represents the 30-60-90 days plan to implement a data warehouse in the company.
Slide 68: This slide highlights title for topics that are to be covered next in the template.
Slide 69: This slide depicts the roadmap for data warehouse implementation in the company.
Slide 70: This slide highlights title for topics that are to be covered next in the template.
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 highlights title for topics that are to be covered next in the template.
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 used in the presentation.
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.