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Executive Information System Powerpoint Presentation Slides

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This complete presentation has PPT slides on wide range of topics highlighting the core areas of your business needs. It has professionally designed templates with relevant visuals and subject driven content. This presentation deck has total of eighty eight slides. Get access to the customizable templates. Our designers have created editable templates for your convenience. You can edit the color, text and font size as per your need. You can add or delete the content if required. You are just a click to away to have this ready-made presentation. Click the download button now.

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Content of this Powerpoint Presentation

Slide 1: This slide introduces Executive Information System. 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 depicts the current situation of our company by displaying the ratio of unstructured and structured data.
Slide 7: This slide presents gap in the organization by showing how big data is causing challenges.
Slide 8: This slide highlights title for topics that are to be covered next in the template.
Slide 9: This slide displays need for a data warehouse in the organization, such as data quality, single point, etc.
Slide 10: This slide shows need for a data warehouse based on business users, storage for historical data, etc.
Slide 11: This slide depicts the data warehouse benefits for organizations such as time-saving, improved business intelligence, etc.
Slide 12: This slide highlights title for topics that are to be covered next in the template.
Slide 13: This slide shows characteristics of data warehouses such as subject-oriented, integrated, time-variant, and non-volatile.
Slide 14: This slide represents the subject-oriented feature of data warehouse and various operational applications.
Slide 15: This slide depicts the integrated feature of the data warehouse and how different subjects are stored.
Slide 16: This slide shows time-variant feature of data warehouses and how they can store years-old information.
Slide 17: This slide illustrates the non-volatile feature of the data warehouse.
Slide 18: This slide highlights title for topics that are to be covered next in the template.
Slide 19: This slide displays the basic architecture of a data warehouse and how information is processed and stored in this architecture.
Slide 20: This slide depicts the three-tier data warehouse architecture, including functions performed.
Slide 21: This slide describes a data warehouse architecture with a staging area.
Slide 22: This slide presents a data warehouse architecture with a staging area and data marts.
Slide 23: This slide shows data warehouse bus architecture and how it decides the flow of the data in the data warehouse.
Slide 24: This slide displays different views of data warehouses, such as top-down view, data source view, data warehouse view, etc.
Slide 25: This slide highlights title for topics that are to be covered next in the template.
Slide 26: This slide depicts the various types of data warehouses, such as enterprise data warehouses, operational data stores, etc.
Slide 27: This slide presents the enterprise data warehouse (EDW) and its architecture, including the data source layer, staging area, etc.
Slide 28: This slide represents the types of enterprise data warehouses such as on-premises data warehouses, cloud-hosted data warehouses, etc.
Slide 29: This slide illustrates the operational data store and its architecture, including data sources such as unstructured and structured.
Slide 30: This slide depicts the data mart type of data warehouse, its architecture, and how a single department manages it.
Slide 31: This slide depicts the dependent data mart and how it can be established in two ways.
Slide 32: This slide presents the independent data mart and has no connection with the central data warehouse.
Slide 33: This slide depicts the hybrid data mart and how data is integrated into this type of data mart other than data warehouse.
Slide 34: This slide highlights title for topics that are to be covered next in the template.
Slide 35: This slide depicts what a cloud data warehouse is and how it can store data from many data sources.
Slide 36: This slide shows the benefits of cloud data warehouses, such as cost reduction, data security, etc.
Slide 37: This slide represents what a modern data warehouse is and how it supports SQL, machine learning, etc.
Slide 38: This slide highlights title for topics that are to be covered next in the template.
Slide 39: This slide displays the critical components of a data warehouse, such as load manager, warehouse manager, etc.
Slide 40: This slide represents the stages of data warehouse such as operational database, offline data warehouse, etc.
Slide 41: This slide represents the most prominent data warehouse solutions such as MarkLogic, Amazon RedShift, and Oracle.
Slide 42: This slide highlights title for topics that are to be covered next in the template.
Slide 43: This slide depicts how the data warehouse works, including how operations such as extraction, transformation, etc.
Slide 44: This slide represents how data warehouses, databases, and data lakes work together.
Slide 45: This slide highlights title for topics that are to be covered next in the template.
Slide 46: This slide represents the guidelines for data warehouse design, such as describing the business requirements, development of conceptual design, etc.
Slide 47: 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 48: This slide depicts the bottom-up design approach of the data warehouse and how data mart is built firstly in this approach.
Slide 49: This slide highlights title for topics that are to be covered next in the template.
Slide 50: This slide depicts the business best practices to implement a data warehouse.
Slide 51: This slide describes the IT best practices for implementing a data warehouse, including tracking performance & security, maintaining data quality standards, etc.
Slide 52: This slide shows Checklist to Implement Data Warehouse in Company.
Slide 53: This slide represents the steps to implement a data warehouse in the organization, including enterprise strategies, phased delivery, etc.
Slide 54: This slide depicts the data warehouse implementation trends such as cloud data warehouse, data warehouse as a service, etc.
Slide 55: This slide represents the autonomous data warehouse with zero complexity deployment and how it will automate the routine.
Slide 56: This slide describes the budget for data warehouse implementation, including storage on the cloud, storage on-premise, etc.
Slide 57: This slide highlights title for topics that are to be covered next in the template.
Slide 58: This slide depicts a comparison between database and data warehouse based on the design, type of information, etc.
Slide 59: This slide displays the comparison between data warehouse and operational database systems based on design, purpose, etc.
Slide 60: This slide depicts the comparison between data warehouse and data lake and how data is stored in the data warehouse.
Slide 61: This slide represents a comparison between data warehouse and data mart and how data marts can be designed for sole operational reasons.
Slide 62: This slide presents the comparison between data warehousing and business intelligence and how business intelligence helps to generate useful output from raw data.
Slide 63: This slide highlights title for topics that are to be covered next in the template.
Slide 64: This slide represents the impacts of data warehouse implementation on the company.
Slide 65: This slide highlights title for topics that are to be covered next in the template.
Slide 66: This slide represents the 30-60-90 days plan to implement a data warehouse in the company.
Slide 67: This slide highlights title for topics that are to be covered next in the template.
Slide 68: This slide depicts the roadmap for data warehouse implementation in the company.
Slide 69: This slide highlights title for topics that are to be covered next in the template.
Slide 70: This slide shows dashboard for data warehouse implementation in the organization.
Slide 71: This slide is titled as Additional Slides for moving forward.
Slide 72: This slide highlights title for topics that are to be covered next in the template.
Slide 73: This slide represents what a data warehouse is, including its different data sources and the operations performed.
Slide 74: This slide displays the OLAP and OLTP in data warehousing and how OLAP tools are used for multifaceted data analysis.
Slide 75: This slide represents the extract transform and load tools of the data warehouse and how they perform their jobs.
Slide 76: This slide depicts the schemas in data warehouses such as star schema and snowflake schema.
Slide 77: This slide represents the massively parallel processing analytical database and how parallel processing is done.
Slide 78: This slide describes the applications of data warehouses in different industries such as banking, healthcare, government, etc.
Slide 79: This slide showcases Icons for Executive Information System.
Slide 80: This is a Comparison slide to state comparison between commodities, entities etc.
Slide 81: This is About Us slide to show company specifications etc.
Slide 82: This slide shows Post It Notes. Post your important notes here.
Slide 83: This slide shows Circular Diagram with additional textboxes.
Slide 84: This slide contains Puzzle with related icons and text.
Slide 85: This slide shows SWOT describing- Strength, Weakness, Opportunity, and Threat.
Slide 86: This slide presents Bar chart with two products comparison.
Slide 87: This slide depicts Venn diagram with text boxes.
Slide 88: This is a Thank You slide with address, contact numbers and email address.

FAQs

Data warehouses have four main characteristics: they are subject-oriented, integrated, time-variant, and non-volatile. This means that they focus on specific subject areas, combine data from different sources, store historical data, and do not allow data to be modified or deleted.

An enterprise data warehouse is a large-scale centralized repository that stores data from across an entire organization, while a data mart is a smaller repository that is focused on a specific department or business function. Data marts are often used to provide quick access to specific data sets, while an enterprise data warehouse is used for broader data analysis and reporting.

Some best practices for implementing a data warehouse include defining clear business requirements, developing a solid conceptual design, ensuring data quality standards are in place, tracking performance and security, and implementing a phased delivery approach.

A data warehouse is needed in an organization to provide a centralized repository for storing and managing large amounts of data from different sources. It helps improve data quality, provides a single point of access for data, and enables better data analysis and reporting.

Big data is causing several challenges in organizations, including difficulties in storing and processing large amounts of data, maintaining data quality, ensuring data security, and analyzing data effectively.

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    by Jake Smith

    Really like the color and design of the presentation.
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    by Miller Rogers

    The content is very helpful from business point of view.

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