When we talk about data preparation, it cleans, blends, and shapes data to get it ready for analysis or tasks like migration. Preparing data is a fundamental part of enterprise systems and applications like data warehouses and business intelligence tools. However, it is also essential for ad-hoc requests, data science algorithms, and IT teams who need high data quality levels.
What is data preparation?
The process of cleaning and transforming raw data is known as data preparation. Typically, it will involve reformatting and correcting existing datasets with the objective of enriching it for business tasks.
As a whole, data preparation can be a time-consuming role, but it is an essential part of ensuring you have high-quality information feeding business decisions. 76% of data scientists say that data preparation is the worst part of their job but appreciate it is fundamental for accuracy and integrity of insight. Some of the key benefits of data preparation are:
- It helps to catch errors quickly before processing
- All data being used in analysis is high-quality and useful
- Better decisions can be made as data is in the right format and accurate
The majority of data preparation services now operate in the cloud, giving them superior scalability, and making them future proof. Organizations do not have to worry about legacy infrastructures with cloud platforms updating automatically and promoting growth.
Some refer to data preparation in the form of the 5D’s; discover, detain, distill, document, and deliver.
The 5D’s of data preparation
We will briefly look at the 5D’s of data preparation before reviewing some of the task’s best tools.
For any project, you want to find the data that is best suited for the purpose. A data catalog will help discover what you have available and is an essential data preparation component.
After discovering data, you need to find ways to collect or detain it.
Following a collection process, the distill phase works through refining the information, ready for its intended purpose,
Anything that is discovered, detained, and distilled will need to be incorporated into documentation. The documents include terminology definitions, usage recommendations, and relationships, amongst other things.
The final phase is to structure the distilled data to be in the right format for processing by the users.
The best data preparation services
While there are many tools and platforms available, below are some of the most popular amongst industry experts.
StrategicDB is a full service data preparation and data cleansing company. Utilizing a combination of machine learning and human workforce allows for full customization.
Alteryx helps users to cleanse and prepare data from warehouses, the cloud, spreadsheets, and just about any other source where it might be stored. The data preparation service allows users to leverage quality, integration, and transformation features via the intuitive Alteryx Designer interface.
The Infogix data preparation services offer data governance capabilities such as glossaries, cataloging, lineage, and metadata management. With the tools, you can create customizable dashboards and workflows that adapt to the organization.
Paxata is a self-service data preparation application. The dashboard offers familiar spreadsheet terms, so it doesn’t feel like you are using a brand new tool. Algorithms will infer what your data means and capture steps for future workflows.
Talend Data Preparation
Talend Data Preparation helps business professionals without advanced technical skills to run processes themselves. The platform makes data preparation the responsibility of everyone rather than relying on expert resources. The aim is to reduce 80% of the time data analysts must spend on data preparation before doing their job efficiently.
Data preparation services are enterprise tools that improve the productivity of whoever uses them. Although the focus is on analytics, clean data impacts every business area from IT to HR, marketing, and sales. Using the tools in this overview will help you foster business collaboration and turn your data into a valuable asset.