What is data preparation, and why is it such an area of importance for modern business? To gain an understanding, let’s consider this relatable scenario:
You’re back in grade school, working on a book report project from your teacher. The assignment is to summarize Robert Louis Stevenson’s classic, Treasure Island, then provide context for real-life pirates from that age. You’ve got a lot of work ahead of you: a book to read, resources to comb, and a paper to write. There’s a lot of preparation before you actually start writing.
Snap back to today, and you’re in the same position at your job. Only this time, instead of a book report, the project is part of your company’s mission-critical operations. Still, there’s a lot of preparation involved, including gathering data, cleansing it, and pulling out relevant data sets to guide your decision-making.
Just like you can’t write a book report without reading the book, businesses can’t drive smart decisions without relevant data. To get it takes data preparation.
What is Data Preparation?
Data preparation is the act of discovering, cleansing, enriching, and transforming raw data to make it usable for application or analysis. In the context of a book report, it’s everything that comes before writing the report. It’s the data science version of reading the book, researching the subject matter, and developing an understanding of the objective.
In preparing data for integration, businesses need to ensure the integrity of that data. It can be a cumbersome process without the right tools – but an essential one. Here are a few examples of data preparation methods:
- Importing raw data from various sources into a single, standardized database
- Enriching source data to provide context or add markers for later analysis
- Cleansing data to remove errors, duplicates, outliers, or corruptions
- Validating data to fill missing values, mask sensitive entries, and finalize
- Transforming data to make it appropriate for analysis or application
- Storing data in an accessible location and format, such as a data warehouse
In short: data preparation is everything leading up to the functional usage of that data. Regardless of the scope of preparation involved, the process ensures the final output is relevant, reliable, and applicable.
The Devil Is in the Details
Businesses, big and small, across every sector of industry, benefit from data preparation. Why? Companies need the best available data to drive decision-making and innovation. Investing time and energy in data preparation increases the likelihood of success for all manner of projects.
Data preparation doesn’t have to be complex to be effective, either. Here’s a simple data preparation example:
ABC Company asks its customers for their birthday month as part of a registration process. People submit answers in different forms: January, Jan., January 3, and with various misspellings. To determine which month is the most popular for birthdays, the company needs to prepare the data consistently with “January.” To do it, the signups are aggregated into a database and a script is run to target variations in each month, swapping them with the standardized version. Then, they run a tally on each month for a final count.
Of course, ABC Company could have saved itself a lot of trouble by just making the field a date-format field — which they’ll do the next time!
Taking the time to prepare data can make a major difference in the efficacy of the results when using data. If you read the entire book Treasure Island, you’ll get the nuances of the plot and all of the story details – unlike reading the CliffsNotes. Preparation leads to the clarity and understanding that ultimately produces a better outcome.
Data Preparation Goes Dynamic
Data integration techniques have advanced in the cloud age. Today, a data warehouse or a data lake can feed dozens of applications and systems that put data to work in innovative ways for companies. But with this level of complexity comes a demand for more agile data.
Modern data preparation needs to happen in real time. For many businesses, this means adopting technologies that allow for the rapid aggregation and preparation of data, like an integration platform as a service (iPaaS) capable of connecting data from multiple sources in real time, and tools like Boomi Data Catalog and Preparation that help organizations bring together data across systems, applications, and people. Batching or scheduled data dumps just aren’t enough to keep up with the speed of business today, which has pushed the concept of dynamic data preparation.
Take the ABC Company example. Real-time data preparation would mean that, as soon as a person submits their response and it reaches a database, the data is automatically standardized and deposited into a repository such as a data warehouse. There, it immediately becomes part of a living system. Someone can go in at any point to grab up-to-the-minute data for a report, to inform a campaign, or to make any important decision based on that specific information.
It’s not hard to imagine how valuable dynamic data preparation is at an enterprise scale. Consider tens of thousands of data points, representing innumerable variables, pulled from dozens of sources, aggregated into one continuously updated data lake. Now, imagine the powerful decision-making capabilities for someone tapping into that data.
Data Preparation Leads To Data Readiness
Let’s return to our school example. Now you need to give an oral report on Treasure Island sometime next week. You put together flashcards about the book’s plot and create a narrative with some facts about pirates. You rehearse in the mirror. When the teacher calls your name, you’ll be ready to deliver a great report – one worthy of an A. Your preparation leaves you ready.
Today, businesses practicing thorough data preparation give themselves the advantage. Whether it’s a new data-driven initiative or an immediate need for analysis, having a well-maintained, continuously updated repository for your data means being able to tap into insights on-demand. No more spending weeks to collect, cleanse, and organize data. It’s there, when and how you need it.
Every business using data benefits from putting in the work to prepare it. With an iPaaS like the Boomi AtomSphere Platform and data readiness capabilities such as Boomi Data Catalog and Preparation and Boomi Master Data Hub, that task is becoming much easier.
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