Tiêu đề PROPOSAL (ENG)_DATALIZE-v1.docx ✅

PROJECT PROPOSAL Date: Aug 2024
DATALIZE JSC DATA SOLUTION PROPOSAL 2 MỤC LỤC I. OVERALL SOLUTION PROPOSAL 3 1. Project Requirement & Objectives 3 2. Proposed Solutions 3 3. List of personnel participating in the implementation 6 4. Implementation process and plan according to Timeline 6 II. SAMPLE PROJECTS & SHOWCASES 7 1. Typical Projects 7 2. Power BI DEMO REPORT 11 III. APPENDIX & REFERENCES 11 1. Power BI Introduction 11 3. Data processing and analytics flows in Power BI 12 4. Information management features, targets and KPIs in Power BI reports 13 5. Sample Power BI features implemented 15 I. OVERALL SOLUTION PROPOSAL
DATALIZE JSC DATA SOLUTION PROPOSAL 3 1. Project Requirement & Objectives is looking for a data system solution that automatically processes discrete data from Oracle NetSuite and Excel files to synthesizes them to be stored in a centralized Data Warehouse and structured into dimensional models for analysis and reporting. The following are some detailed contents of the solution that requires:  Requirement: The solution requires building a Data Warehouse system to connect data from Oracle NetSuites about projects, leasing tenants and other accounting and finance calculation with related fees and loans. Besides that it should also connect and map data from Excel for assumption or financial modeling and reporting.  Objectives: The data warehouse system needs to ensure: o Connect and migrate data from NetSuite into Data Warehouse with schedule load o Connect and migrate data from Excel in fixed format into Data Warehouse o Automatically calculate or map data between Excel and NetSuite o The Data Warehouse system needs to store raw data from sources o The Data Warehouse system needs to re-architect data tables for easy analysis o The system needs to easily integrate with Power BI for analysis and reports  Solution: Based on requirements, we consult following solutions o Solution 1: Utilize PowerBI to connect and model report from both sources o Solution 2: Build Data Warehouse to aggregate the data and become source for Power BI  Timeline: The total expected implementation time is o Weeks 1 – 4: o Weeks 2 - 7: o Week 8: o After Week 8:  Delivery: o The data system is built on the company’s system and account o The data is designed according to Data Warehouse architectural standards o Professional documents and project progress content are handed over to customers o Instructions for using the solution and training materials for personnel to operate 2. Proposed Solutions Based on customer requirements and analysis of data as well as current data mining status, we consults a number of solutions including the use of Power BI as a mini data warehouse to aggregate data and analyze to build reports or better is to construct a data warehouse as a centralized source for Power BI. Solution 1: Connect data from Oracle Netsuites and Excel to Power BI directly Solution 1 is based on Power BI and migrate data from both Netsuites and Excel directly into Power BI. This is a quick solution and can build multiple data model for each reports and topics.  Strength: 1. Simplicity: With Power BI Desktop, you can easily connect to the ever-expanding world of data. It’s fast and easy to implement. 2. Variety of Data Sources: Power BI Desktop can connect to many different types of data sources, including basic data sources like Excel files, and online services like Salesforce, Microsoft Dynamics, Azure Blob Storage, and many more6. 3. Cost saving: Save cost from Azure Data Storage Licenses and require only Power BI to develop and deploy so only need Data Analyst to implement, not Data Engineer  Weakness: 1. Limited Scalability: While Power BI is excellent for visualizing and analyzing data, it may not scale as well as a dedicated data warehouse when dealing with very large datasets.
DATALIZE JSC DATA SOLUTION PROPOSAL 4 2. Dependence on Data Quality: The quality of insights generated by Power BI is heavily dependent on the quality of the input data. If the data is not well-prepared or cleaned, it could lead to misleading results.  Consultancy: this is the easy way that can be implemented but Power BI has limitation when connecting data from Netsuites such as saved search data. And when ETL data from Netsuites to PowerBI, if the data table is too large, there will be time-out problems and we may need to limit the data into Power BI. Other than that, this is a good option to create Power BI reports right away and only need Power BI skills to implement and monitor. Figure 1 : Solution 1 Architecture Different way to implement Power BI and Licenses 1. Deploy the use of a common Free account for each Team (one account per Team) and reports will be created and posted to these accounts independently (do not view the same reports). This method is cost-effective, but users share the same account so they will view the same and because it is a Free account, the reports will be viewed separately, meaning if there is a common report, they will have to upload it to 2 places. 2. Deploy the use of a common Pro account for each Team (each Team has a Pro account) to be able to view Workspaces together and view them separately, thereby allowing reports to not be managed twice and can be applied at the same time. Use data decentralization. 3. Deploying the use of 1 Pro account for each important user can allow the creation of common and separate Workspaces for each group and allows independent viewing by users without being affected by the same account. In addition, Pro will be able to use many features with details listed below (Suitable for the number of users <=10) Solution 2: Build Data Warehouse with Azure Data Storage Solution 2 is based on Azure Services to help build Data Warehouse layers and use Data Factory to automatically migrate data from NetSuites and Excel files. The data warehouse can have multiple layers such as staging layers and dimensional model layers. The data will be process and calculate automatically to prepare a good model for Power BI to create reports.  Strength: 1. Scalability: Azure Data Storage offers elasticity, allowing you to handle computation and storage resources independently. This means you can scale your data warehouse as your business grows. 2. Integration: Azure Data Storage is tightly integrated with potential consumers of your fused datasets, like Power BI report or Azure Machine Learning. 3. Control: You have control over the level of security of your data and can customize it to your business’s needs.