AI, mainly used for data automation, has certainly become the hallmark of the digital transformation strategy. According to IDC, global AI spending is forecasted to reach $500 billion in 2024 with a CAGR of 17.5%. Likewise, Gartner predicts low-code application platforms (LCAP), robotic process automation (RPA) and AI are fueling the growth for hyper-automation, and the market is predicted to reach $596 billion in 2022, up nearly 24%.
Robotic Data Automation
In order to solve these challenges, it is important to work with an ecosystem that can automate data integration and data preparation activities. However, data automation is not a simple task. It requires you to have a proper automation instrument that can test data quality, scrub data from errors and map attributes. Additionally, an effective solution must be able to parse data from unstructured formats and database schemas, detect duplicates (a common problem in building AI) and determine whether datasets contain enough information to address the desired use cases.
In the last several years, a wide range of data automation solutions has been created to tackle these challenges. One of the latest ones is the Data Automation Platform (DAP). DAP allows companies to execute end-to-end data preparation in minutes instead of days, automates multiple ETL processes, and it also allows non-technical users to access all data sources and business applications. Thanks to its unique business rules engine, DAP is fully customizable and extremely easy to use.
Drilling Down into Data Automation
To understand more about how the Data Automation Platform works in practice, let’s walk through an example. A large retail company has thousands of sales and inventory locations across the country. For its e-commerce business, the company must store and access customer data in a central place.
This is where the problem begins. For one, the client’s e-commerce platform is only available for a handful of browsers and devices. Another serious issue is that customer data has to be stored in a highly available infrastructure to prevent any major disruption to customers’ orders. Finally, there are many different formats in which customer data is stored throughout its lifecycle, from individual records to legacy systems.
The solution? DAP allows centralized business applications to access all relevant information from multiple sources (which can be as broad as cloud services or as specific as specific retailers’ applications) and make it possible for developers to create new analytical tools. This will allow the retail company to correctly store and use customer data and create an online shopping platform that will meet its customers’ expectations.
The Bottom Line on Data Automation
The growing demand for automation in a variety of industries is becoming a real business imperative. Companies that fail to keep up with this trend are likely to be outperformed by competitors. Fortunately, businesses today have access to advanced technologies, such as DAP, which aim at reducing costs and increasing the efficiency of processes related to automation.
Interested in reading more about AI’s benefits in business? Cloud Computing Benefits – Why You Should Work in the Cloud discusses the benefits of running a business through the cloud.
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