Collecting and organizing all your data in a data warehouse is the first step towards harnessing the power of data analytics.
However, creating a data warehouse is a complex task requiring much technical knowledge. Finding experienced engineers with the skills to build a reliable and organized central data warehouse takes time and effort.
However, organizations need to pay more attention to resources in this process. The data warehouse is the foundation of any data strategy. The single source of truth powers BI tools and provides accurate information on which business decisions are based.
The good news is that by automating many of the complex tasks associated with creating, deploying and maintaining a data warehouse, you can reduce resource requirements and improve the quality of your results. Here’s how to create an automated data warehouse.
Data Warehouse Automation: Definition
The obvious economic benefits and increased data processing speed, accuracy and efficiency are revolutionizing traditional data warehouses through data warehouse automation (DWA). Data warehouse automation aims to automate all automatable aspects of the data warehouse, allowing the project team to focus on the parts of the data warehouse and BI processes that require human intelligence. Rather than having the team manually write all the ETL code that takes months to complete, DWA streamlines the data warehouse project process by automating virtually the entire lifecycle, reducing manual coding and simplifying repetitive and intensive tasks. As a result, BI deployments are almost five times faster.
How Data Warehouse Automation Work
To automate your data warehouse, you need a project plan. You must conduct a risk assessment, involve stakeholders, define goals and deliverables, and develop a project plan.
Create a team and select one or more project leaders. Prepare a schedule, implementation plan and project plan. Then, an implementation plan will be developed based on input from all levels of management, including warehouse managers and supervisors from all areas. Finally, decide which warehouse automation option best meets the organization’s objectives, customer needs, staff requirements, time constraints and available resources. When considering automation options, research them and ask for a demonstration. For example, the criteria for implementing mobile barcode scanning differ from those for implementing a warehouse management system.
Five Simple Steps to Automate Your Warehouse
To get started with warehouse automation, follow the five-step sample plan below.
#1. Set Up an Implementation Committee
Please set up a committee of internal stakeholders familiar with the warehouse’s current resources, challenges and performance, and technology gaps. Consider bringing in external experts who understand supply chain automation and know the industry and warehouse processes.
#2. Gathering The Right Information
Successful warehouse automation requires information about the supply chain and business-critical warehouse operations. Before implementing new automation technologies, You must assess your current infrastructure and data collection methods. We recommend that you delegate responsibility for data migration to an experienced IT team.
#3. Analyze Your Inventory Management Practices
Inventory management is a key component of warehouse operations. Before implementing a warehouse automation system, standard operating procedures (SOPs) for inventory management should be developed or improved. SOPs should be designed to reduce inventory and customer satisfaction and ship, receive, and purchase. Identify key performance indicators (KPIs) that will be used to measure the effectiveness of automated inventory management systems and procedures. Analyze the current inventory control system (e.g. periodic or perpetual system) and assess the impact of automation on this system. See the Inventory Management Guide for more information.
#4. Use Of a Warehouse Management System (WMS)
The software modules of the WMS platform help you track and control inventory, manage warehouse operations, reduce labor costs and improve customer service. A modern WMS must be compatible with modern business applications and mobile devices.
#5. Choose The Type of Warehouse Automation
Is your goal to use automation to reduce the work associated with accounting and inventory management and simplify manual data entry? Or, are you looking to add new locations or increase the size of your warehouse and think it’s time to automate advanced physical processes, such as robots and PGD systems? Determining which warehouse automation suits your goals and customers’ needs is essential.
Example Of Data Warehouse Automation
Take the case of Gamiphi, a retail company with a network of stores in the United States. Gamiphi sells a wide range of toys from different manufacturers. The company uses SQL databases to collect information such as purchases and invoices, inventory data from suppliers, and employee and customer data from stores nationwide. Requests for BI data from IT teams meant waiting several weeks for data to be created, implemented and delivered and additional time to set up or input the necessary data. Gamiphi began looking for automation and data warehouse providers to reduce the time required to collect data.
Summary
Thanks to this blog, you now understand data warehouse automation well. You also know why data warehouse automation is essential for the overall architecture of a data warehouse automation system. In addition, you’ve learned about some popular data warehouse automation solutions that will serve you well in the future when you need them for your data warehouse initiatives.
