Management Information System Powerpoint Presentation Slides

Slide 1: This slide displays title i.e. 'Management Information System' 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 two 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 stored in the database.
Slide 7: This slide describes the gap in the organization by showing how big data is causing challenges and how a data warehouse will help provide solutions.
Slide 8: This slide depicts title for three topics that are to be covered next in the template.
Slide 9: This slide represents the need for a data warehouse in the organization, such as data quality, single point for all data for all users, etc.
Slide 10: This slide describes the need for a data warehouse based on business users, storage for historical data, make strategic decisions, etc.
Slide 11: This slide depicts the data warehouse benefits for organizations such as time-saving, improved business intelligence, improved data quality, etc.
Slide 12: This slide depicts title for five topics that are to be covered next in the template.
Slide 13: This slide represents the 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 and data warehouse subjects sales, product, etc.
Slide 15: This slide depicts the integrated feature of the data warehouse and how different subjects are stored within one place in the data warehouse.
Slide 16: This slide describes the time-variant feature of data warehouses and how they can store years-old information, and users can easily access that information.
Slide 17: This slide illustrates the non-volatile feature of the data warehouse, and it doesn’t support operational data changes such as update, insert and delete.
Slide 18: This slide depicts title for six topics that are to be covered next in the template.
Slide 19: This slide depicts the basic architecture of a data warehouse and how information is processed and stored in this architecture through metadata, etc.
Slide 20: This slide depicts the three-tier data warehouse architecture, including functions performed at the bottom tier, middle tier tasks, tools used at the top tier.
Slide 21: This slide describes a data warehouse architecture with a staging area and how staging helps clean and process the information.
Slide 22: This slide depicts a data warehouse architecture with a staging area and data marts and how it can be used for different groups within an organization.
Slide 23: This slide describes the data warehouse bus architecture and how it decides the flow of the data in the data warehouse, such as inflow, outflow, etc.
Slide 24: This slide describes the different views of data warehouses, such as top-down view, data source view, data warehouse view, and business query view.
Slide 25: This slide depicts title for eight 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, and data marts.
Slide 27: This slide describes the enterprise data warehouse (EDW) and its architecture, including the data source layer, staging area, data storage layer, etc.
Slide 28: This slide represents the types of enterprise data warehouses such as on-premises data warehouses, cloud-hosted data warehouses, and hybrid data warehouses.
Slide 29: This slide illustrates the operational data store and its architecture, including data sources such as unstructured and structured, ETL operations, and applications.
Slide 30: This slide depicts the data mart type of data warehouse, its architecture, and how a single department manages it in an organization.
Slide 31: This slide depicts the dependent data mart and how it can be established in two ways, such as access to both data warehouse and data mart, etc.
Slide 32: This slide represents the independent data mart and has no connection with the central data warehouse, and is best suited for small groups or departments.
Slide 33: This slide depicts the hybrid data mart and how data is integrated into this type of data mart other than data warehouse and valuable for ad hoc integration.
Slide 34: This slide depicts title for three 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 and is scalable as per the organizational needs.
Slide 36: This slide shows the benefits of cloud data warehouses, such as cost reduction, data security, 99.99% reliability, etc.
Slide 37: This slide represents what a modern data warehouse is and how it supports SQL, machine learning, graphs, spatial processing, etc.
Slide 38: This slide depicts title for three topics that are to be covered next in the template.
Slide 39: This slide represents the critical components of a data warehouse, such as load manager, warehouse manager, query manager, and end-user access tools.
Slide 40: This slide represents the stages of data warehouse such as operational database, offline data warehouse, real-time data warehouse, and integrated data warehouse.
Slide 41: This slide represents the most prominent data warehouse solutions such as MarkLogic, Amazon RedShift, and Oracle, along with their characteristics.
Slide 42: This slide depicts title for two 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, and loading are performed on data in the data warehouse.
Slide 44: This slide represents how data warehouses, databases, and data lakes work together to process the data and carry out beneficial outputs.
Slide 45: This slide depicts title for three 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 represents 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 depicts title for seven topics that are to be covered next in the template.
Slide 50: This slide depicts the business best practices to implement a data warehouse, including describing the required data, team building, etc.
Slide 51: This slide describes the IT best practices for implementing a data warehouse, including tracking performance & security, etc.
Slide 52: This slide describes the checklist to implement a data warehouse in the company, including strategies to assess data, organization of data, etc.
Slide 53: This slide represents the steps to implement a data warehouse in the organization, including enterprise strategies, phased delivery, and iterative prototyping.
Slide 54: This slide depicts the data warehouse implementation trends such as cloud data warehouse, data warehouse as a service, and data warehouse deployment.
Slide 55: This slide represents the autonomous data warehouse with zero complexity deployment and how it will automate the routine and monotonous tasks.
Slide 56: This slide describes the budget for data warehouse implementation, including storage on the cloud, storage on-premise, BI and ETL tools, HR, etc.
Slide 57: This slide depicts title for five 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 both stores, data sources, data availability, etc.
Slide 59: This slide depicts the comparison between data warehouse and operational database systems based on design, purpose, data storage orientation, performance, etc.
Slide 60: This slide depicts the comparison between data warehouse and data lake and how data is stored in the data warehouse as well as data lakes.
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 represents the comparison between data warehousing and business intelligence and how business intelligence helps to generate useful output from raw data.
Slide 63: This slide depicts title for the topic that is to be covered next in the template.
Slide 64: This slide represents the impacts of data warehouse implementation on the company and how it enhances the productivity of employees and decision-making.
Slide 65: This slide depicts title for the topic that is 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 by including the tasks performed in the implementation process.
Slide 67: This slide depicts title for the topic that is to be covered next in the template.
Slide 68: This slide depicts the roadmap for data warehouse implementation in the company by describing the steps to be performed while implementing a data warehouse.
Slide 69: This slide depicts title for the topic that is to be covered next in the template.
Slide 70: This slide represents the dashboard for data warehouse implementation in the organization, including transactions per hour and value, total value by the day, etc.
Slide 71: This slide presents title for additional slides.
Slide 72: This slide depicts title for six 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 on that information.
Slide 74: This slide represents 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 on the stored information in the data warehouse.
Slide 76: This slide depicts the schemas in data warehouses such as star schema and snowflake schema and how they store information within a data warehouse.
Slide 77: This slide represents the massively parallel processing analytical database and how parallel processing is done across multiple servers.
Slide 78: This slide describes the applications of data warehouses in different industries such as banking, healthcare, government, education, insurance, etc.
Slide 79: This is the icons slide.
Slide 80: This slide highlights comparison of products based on selects.
Slide 81: This slide shows about your company, target audience and its client's values.
Slide 82: This slide depicts posts for past experiences of clients.
Slide 83: This slide presents circular diagram.
Slide 84: This slide displays puzzle.
Slide 85: This slide highlights SWOT of the company.
Slide 86: This slide exhibits quarterly bar graph for different products. The charts are linked to Excel.
Slide 87: This slide displays Venn.
Slide 88: This is thank you slide & contains contact details of company like office address, phone no., etc.