How Data Warehouse Automation Tools Can Expedite Your Data Processes

Data warehousing is growing in popularity as more and more organizations are looking into developing EDWsfor data storage and reporting. With the global data warehousing market expected to reach $51.18 billion by year 2028 growing at a CAGR of 10.7%, organizations are more convinced in investing in data warehousing products and realize the benefits they can derive through them. Let’s dive deeper to understand why data warehousing is becoming a widely used option for data storage and how data warehouse automation tools can speed up your data processes.

What is data warehousing and why do we need data warehouse tools?

Data warehousing is the process of collecting, storing, and managing data from disparate sources to provide meaningful insights. A data warehouse essentially serves as a data storage repository where data from multiple sources is integrated and stored. The main purpose of a data warehouse is to standardize, streamline and speed up the business intelligence process.

Modern data warehouse automation tools are equipped with the ability to reduce the need for manual intervention especially for repetitive and time-consuming tasks. Companies leverage these automation tools to speed up their data processes and gather crucial insights faster.

Benefits of Using a Data Warehouse Automation Tool

Here are a few ways in which data warehouse automation tools expedite your data processes:

  1. Reduced development time: Data warehouse automation tools substantially reduce your development time by cutting down repetitive tasks.
  2. Automation at each step: With DWA, users can automate processes at each step. From designing, developing, deployment, and monitoring, a DWA tool can automate your repetitive tasks throughout the way. With all recurring, time-consuming tasks, automated, the process becomes simplified and even business users are empowered to use data while allowing IT teams to focus on more crucial problems.
  3. Improved data quality: Data quality is crucial for reliable business analytics and sound insights. It is important to cleanse and validate the data coming in from multiple sources before it can be further processed and used for reporting. Hence, with a DWA tool, users can predefine data quality rules and checks to assure data quality for a more reliabledata warehouse architecture.
  4. Faster reporting: Data warehouse automation ensures faster data integration with automated ETL process, consequently leading to faster time to insights. With near real-time access to data, business units can drive their own relevant insights for faster decision making.

What Should You Look for in a Data Warehouse Automation Tool?

The demand for data warehouse automation tools has been growing which is why there are plenty of options available in the market. Here are some features and capabilities you should look for while choosing a scalable and agile DWA tool.

  1. High performance ETL

A data warehouse tool must be equipped with a high performance ETL engine to ensure quick data integration from multiple sources and the ability to accommodateincreasing amounts of data.

  1. Data Cleansing

Companies generally use data warehouses to maintain historical records for business decisions. When dealing with high volumes of historical data, it is essential to ensure that only relevant data is loaded into the data warehouse.With data cleansing capabilities, you can ensure that you are only using data you really need for reporting and analysis, allowing for faster decision-making.

  1. Integrations

Organizations today need to leverage data from several different sources such as cloud sources, databases, etc. With growing volumes of data coming from heterogenous sources, it is crucial for the DW to be able to integrate data from all different applications and information systems in near real-time so that decisions can be made in a timely manner.

  1. Code-free Data Modeling

Modern data warehouse tools have code free interfaces that allow users to perform tasks such as creating data models and data pipelines with just a few clicks. This makes the whole data warehousing process much simpler and empower business users to take charge.

With rising data warehouse automation needs, it’s imperative that organizations choose a data warehouse automation tool that fulfills all their requirements. Adding automation at the core of your data warehouse architecture, is going to greatly boost productivity and faster business intelligence.


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