TidyData is a company that offers data monitoring for the ETL process. We have engineered a system that integrates with all ETL tools and provides multiple checks on your data pipeline. If there is something wrong in the system, you’ll be notified.
Our customers use ETL systems to extract, transform, and load data into their data warehouses. When something is inconsistent in the process, it leads to poor analytics. If there is a problem when the information is collected and aggregated, it will create holes in the information.
Here’s a look at what an ETL system does and how we make certain that it is doing its job.
What is ETL?
ETL is short for extract, transform, load, which is the general procedure it takes to copy data from a single source or multiple sources into a system. The program will take the data that it collects and run it through a set of rules that may include (aggregation, validation, transformation) into information to import into the destination database or data warehouse.
Companies need this type of process, because they often collect information in different systems that are not compatible with one another. ETL solves that problem so that they can continue using the different types of programs and formats while compiling the extracted data into information stored in one central location.
Why Is The ETL Process Important?
Many companies, especially larger ones that have engineering teams, leave their data extraction and storage up to the engineering team. Unfortunately, this creates an inefficient system that tends to be full of errors. Also, it makes it difficult to scale the amount of data the company needs to collect,store and process.
The ETL process reduces human error and creates a process that is easily scalable. This frees up the engineering team to focus on other aspects of the business.
Use Cases For ETL
There are several use cases for ETL tools such as data integration, data warehousing, and data migration.
Integration - this allows the information stored in different systems to update as changes are made on one platform or another. Migration - if you need to update your system or switch to a new system, moving the data can be a logistical nightmare. No one wants to lose their valuable information, which is why ETL tools are necessary. They automate the transfer of data.
What is Better ELT or ETL?
ETL stands for extract, transfor, and load which is a different process than ELT, where the information is loaded into the data warehouse before being transformed.
The ETL process for extensive data cleansing prior to loading the information in the target system was traditionally used to process data into a data warehouse. With the introduction of high powered data warehouses such as Redshift and Snowflake, ELT was introduced. The data would be loaded into the warehouse and the transformation would take place in the data warehouse, with SQL.
How Extract, Transform, and Load Work
This process has five basic steps that are followed when collecting data from raw sources and turn it into insights. . Here are the different steps:
While almost any data storage can be used for this process, most often they are flat files which have a single table of data. Or, they are Relational Database Management Systems (RDBMS) that is made up of rows and columns. The data can be extracted in several ways depending on the system including: Updating - when modifications take place to the source records, it will provide a notification that the records have been changed. Incremental - some systems do not give a notification of the updates made. In this case, the system identifies the changes and propagates it down. Full extract - some systems keep a copy of the last extract in order to identify what changes were made.
After the data is extracted and converted into the right format for the system, the data must be transformed to fit the business rules. This could include sorting, filtering, cleaning data, and other actions. During the transformation process, data is joined from several different sources. Also, it requires sorting, applying validation rules, and generating aggregates to name a few. This part of the process will set up unification rules like: Make a standard form for zip codes and phone numbers, Validate address fields and convert them to the correct naming, Make identifiers such as gender categories unique Convert null values into standardized values
When the data has been transformed, it will need to be loaded into the target destination. This could be a database or data warehouse where the information will be stored for use.
What is an ETL Process Example?
One of the most common examples of this process is when organizations need to merge historical and current data before loading into a data warehouse. As new information is collected, the system updates the data warehouse.
What Are Data Warehouses?? How Does a Data Warehouse Work?? Data Warehouses Tidy Data Supports? Two of the data warehouses we support include Amazon Redshift and Snowflake. Here is a look at these two systems: They support thousands of customers including Lyft, Yelp, Intuit, McDonald’s, and more. Their systems have proven to be able to grow with businesses as they have gone from startups to multi-million dollar corporations. With Redshift you are able to query petabytes of data, both structured and semi-structured across your data lake and data warehouse using Standard SQL. You are also able to save the results from your searches into an S3 data lake. The Snowflake data warehouse uses a custom SQL database engine and offers unique capabilities to its customers. This analytic data warehouse is offered as a SaaS (software-as-a-service) product and allows for faster, user-friendly functionalities to that of traditional data warehouses. There is no hardware needed to run Snowflake either virtual or physical. This is a cloud-based service that has ongoing maintenance and management handled by the team. ETL Monitoring? When there are flaws in the ETL process, it can cause you to receive bad information or delays on the transfer. For example, if you are pulling data from two different sources that have inconsistencies in how they collect data, it can confuse the ETL tool. Hand-correcting the errors can be tedious and not reliable. That’s why you need a monitoring tool to streamline and automate the process. Monitoring tools are set up with the ability to detect anomalies in the information it is collecting. AI machine learning is paired with monitoring tools to see when numbers get out of alignment and adjustments that need to be made. AI Machine Learning Alerts You to Pending Problems? AI Machines never sleep or take a break, meaning they are constantly monitoring the data that comes in through the ETL tools. As it picks up on the anomalies in the information, it can be programmed to alert specific departments or the architect of the system that there are problems that must be fixed. With monitoring in place, data can be more accurate. What’s the Difference Between a Data Pipeline and Data Warehouse? The ETL Pipeline is the process that involves extracting the data from the source and transforming it before it is loaded into the data warehouse. The warehouse stores the information in a readable dashboard that can be searched by the user. We Monitor Your ETL Pipeline In order to get accurate information in your data warehouse, the data pipeline must be free from errors. Our system is easy to set up and immediately gets to work on detecting anomalies in the data pipeline that can keep the information from loading into the data warehouse. With our real-time monitoring solution, you will be alerted to any issues in your ETL system. How Tidy Data Can Help Your Business Here at Tidy Data, we help companies by protecting their investments in their data pipelines. We do this by making sure that the process runs error-free and the data is accurate. Without accurate data, a business will lose money and create major problems in the company. Utilizing an engineering team to create a custom solution winds up with many errors, not to mention it is highly labor-intensive. That means it is not a scalable or viable solution, which will limit you from being able to increase your sales and production. We offer a hosted solution to make sure that monitoring is set up quickly, easily, and can scale as the company grows. Our AI driven monitoring system will allow you to get the consistent format needed to accurately extract and process your data. Contact us Today
Please reach out to the experts at Tidy Data today. We’ll be happy to answer your questions and provide you the ELT services you need. Contact us now and one of our experts will get back to you as soon as possible.