Streamline your ETL Process with Sourcetable

What is Visio?

Visio is a diagramming tool developed by Microsoft. As a Microsoft 365 app, it enables users to create a variety of diagrams, including flowcharts, org charts, floor plans, and network diagrams. Visio is designed to provide a robust platform for creating detailed and professional diagrams that can be used in a commercial setting.

The software offers a wide range of premade templates and thousands of customizable shapes to assist in diagram creation. With its integration into Microsoft 365, Visio brings the power of this suite to enhance its diagramming capabilities, including advanced features for data visualization, process execution, and collaboration.

Available to Microsoft 365 commercial subscribers, Visio supports both desktop and web app formats. The desktop app allows for drawing and annotating with a finger or pen, and data linking with Microsoft products and other data sources. Visio for the web, included with Visio Plan 1 and Plan 2, allows users to view, create, and edit diagrams directly in the browser, inheriting Microsoft 365's security, accessibility, and compliance features.

Visio maintains compatibility with older versions while also upholding security by automatically blocking pre-2013 files. It includes Information Rights Management (IRM) features to protect the integrity of diagram files. Whether through a 30-day trial or volume licensing, Visio is accessible to its users in various formats, backed by the support of Microsoft.

ETL Tools for Visio

Azure Data Factory and SQL Server Integration Services (SSIS) are common ETL tools that facilitate the Extract, Transform, and Load process, which is a data pipeline designed to collect data from multiple sources, transform it according to business rules, and load it into a destination data store. ETL involves a specialized engine for data transformation and often uses staging tables for temporary data holding. It performs transformations by filtering, sorting, aggregating, joining, cleaning, deduplicating, and validating the data.

ELT, standing for Extract, Load, and Transform, is a variant of ETL where the data is transformed directly in the target data store, which can be beneficial for big data scenarios. ELT skips the data copy step present in ETL and is effective when the destination system can efficiently handle the transformation workload, often converting the source data into a format optimized for queries.

When comparing ETL tools, IBM's Information Server Infosphere platform is noted for its strong vision and flexibility, while Informatica is recognized for its substantial size, resources, and consistent track record. Microsoft's SQL Server Integration Services is well-supported with broad documentation, and Oracle's tools are typically used for batch-oriented work. Various other vendors like SAP BusinessObjects, SAS, Sun Microsystems, Tibco, ETI, iWay Software, Pervasive Software, Open Text, and Pitney Bowes Software offer specialized features, from multi-management and message-oriented integration to data integrity, quality, and metadata utilization.

Streamline Your ETL Process with Sourcetable

Choosing Sourcetable for your ETL processes, particularly when working with data from Visio, provides a seamless and efficient path to integrate your data directly into a spreadsheet-like interface. Instead of relying on third-party ETL tools or investing time and resources into developing a custom ETL solution, Sourcetable offers a straightforward alternative that syncs your live data from almost any application or database.

With Sourcetable, the complexity of ETL is significantly reduced. Its capability to automatically pull in data from multiple sources, including Visio, allows you to bypass the intricate steps typically associated with the transform phase of ETL. This not only saves valuable time but also minimizes the potential for errors. Furthermore, Sourcetable's familiar spreadsheet interface is ideal for those who are accustomed to the flexibility and functionality of traditional spreadsheets, making it an excellent tool for automation and enhancing business intelligence without the need for specialized training.

Common Use Cases

• V

  
  Use case 1: Automatically creating a flowchart in Visio from an Excel workbook to visualize the ETL process
• V

  
  Use case 2: Using Visio to document the logical flow of data through various transformation stages within an ETL workflow
• V

  
  Use case 3: Exporting a Data Visualizer diagram and associated Excel workbook to a Visio template package for easy sharing and replication of ETL processes
• V

  
  Use case 4: Utilizing two-way synchronization between Visio and Excel to maintain up-to-date ETL process documentation

Frequently Asked Questions

What does ETL stand for and what does it do?

ETL is short for 'extract, transform, and load'. It is a data pipeline used to collect data from various sources, transform the data according to business rules, and then load it into a destination data store.

What are the most common transformations involved in an ETL process?

The most common transformations include data conversion, aggregation, deduplication, filtering, cleaning, formatting, merging/joining, calculating new fields, sorting, pivoting, lookup operations, and data validation.

How do third-party ETL tools like SSIS improve the ETL process?

Third-party ETL tools like SSIS offer faster and simpler development than SQL scripts, can be used by people with wide business knowledge, and are able to join data from multiple files on the fly.

What is the purpose of a staging area in an ETL process?

A staging area is an optional intermediate storage area used for auditing, recovery, backup, and load performance purposes within an ETL process.

What is the difference between ETL and ELT?

The main difference is the order of operations. ETL stands for 'extract, transform, and load' while ELT stands for 'extract, load, and transform'. In ELT, the transformation occurs in the target data store and skips the data copy step present in ETL, making use of external tables, massively parallel processing, and optimized storage formats like Parquet.