Data preparation is cleaning, structuring and enriching raw data into a desired output for analysis. It’s commonly referred to as “janitorial work,” but is enormously important and mission-critical to ensure robust, accurate downstream analytics. Properly conducted, data preparation gives you insights into the nature of your data that then allow you to ask better questions of it.
These are the main activities in the data prep process that can help companies utilize data to find key insights:
Once the raw data has been cleaned and prepared, it can then be analyzed and used to make decisions and find patterns. As straightforward as data preparation sounds, there are challenges that can cause some companies to neglect data prep or skip over crucial steps.
One of the biggest challenges with preparing data is that, historically, it has been very time-consuming. It has been widely publicized that up to 80% of the overall analysis process is spent cleaning or preparing data. As data has increased in size and complexity in recent years, however, data preparation has only grown more demanding and is often relegated to the organization’s most technical employees.
But when data preparation lives behind technical barriers, this presents new challenges: first, the organization’s most costly resources are tied down with preparing data and are unable to solve more challenging data problems. Second, business analysts, or those who know the data best, are unable to get involved with the preparation process themselves. They lack the visibility into their raw data, which has the potential to transform their requirements and, ultimately, their analysis.
Self-service data preparation tools, such as Trifacta, are solving these problems and carving out a new market with huge demand. By empowering non-technical users with the ability to wrangle data themselves, organizations can unlock huge value from their big data investments. Business units and organizations can spearhead their own initiatives, leveraging new data sources while maintaining the same resources on their team. Simultaneously, Wrangler accelerates the process, allowing businesses and organizations to arrive at insights faster.
Benefits of These Self-service Tools
The technical employees only have so much time to work, and that can often lead to data preparation taking a back seat. Some businesses might also not have the funding to pay IT and data specialists to work on data prep. These shortages highlight why self-service data preparation is crucial for many organizations.
Self-service data prep platforms like Trifacta are designed to be used by employees that don’t have an extremely technical background. Trifacta can be used with ease by those who have business backgrounds, or other less technical backgrounds, and it is specifically designed for ease of use. Self-service tools accelerate the data prep process because it expands who can work on the preparation, and the acceleration helps companies reach unexpected opportunities and new patterns that can drive future success.
In the modern age of data, data is no longer stored solely on a server. Most organizations are utilizing the cloud to store data. To transition data in the cloud, businesses face the same challenges: shortages of qualified personnel and time to prepare the data. But using self-service tools such as Trifacta, companies are able to utilize the benefits of having data in the cloud. Unprepared data is hard to integrate with the cloud or machine learning because there are still anomalies and null values that make the data hard to use. But with self-service tools, companies are able to prepare the data efficiently and accelerate the process of putting the prepared data in the cloud.
With Trifacta, businesses are able to accelerate and prepare data from data lakes and warehouses and multi-cloud environments for AI and machine learning initiatives. In the modern world of data, it’s key to be able to use the prepared data in multiple environments and have quality integration with the cloud. Trifacta’s data preparation helps organizations prepare raw data for the crucial next steps of integration and machine learning.
Trifacta has an innovative approach to self-service data preparation, which we call “data wrangling.” Trifacta’s intuitive interface combines interactive exploration, or the ability to visually profile data, with predictive exploration, or suggested transformations that gain intelligence with each new click. What’s more, every transformation step defined by the user in Trifacta is logged and at execution time automatically compiles down into the appropriate processing framework. With Designer Cloud, data preparation is accessible, intuitive and scalable across the organization. Sign up today!
