Data preparation is a survival basic. Alright, maybe you wouldn’t pick an efficient data prep tool as the one item you’d want to have if you were deserted in the jungle. But when talking about everyday business — which is wild in its own way — organizations are becoming very reliant upon data insights, and it’s apparent that efficient data preparation is super critical.
Simply collecting vast amounts of data is not enough to unlock the potentially massive value that the data holds. And, particularly when targeting the success of complex machine learning (ML) initiatives, securing quality data from reliable and replicable preparation processes is a must-do. The higher the quality of the data that you end up training your models on, the more accurate and robust your models will be. On the flip side of that with low-quality data, well … it’s not hard to figure out what happens there.
So, where can you get what you need in order to set yourself up for success? Dataiku. With data preparation tools crafted as a key capability of the platform, Dataiku allows individuals with varying levels of technical expertise to connect, cleanse, and prepare data for analytics and ML projects at scale in the easiest way possible.
Your Data Prep To-Do List
- Gathering
- Cleaning
- Aggregating
- Structuring
- Exploring
What Needs to Happen
For the best outcome, teams need to be able to perform transformations in their preferred way with the freedom to easily apply powerful recipes that will let them quickly analyze and prepare data for downstream analysis. They also need to have the ability to automate time-consuming repetitive tasks involved in data preparation, so that their time can be reallocated to interpreting the valuable insights they gather.
By tapping into the capabilities of Dataiku, getting your data ready and managing recipes to derive meaningful results from your raw data across various sources can and should be turned into an efficient and repeatable process. Additionally, more key stakeholders across your organization can review and contribute input to processes from the get-go.
The Apparatus Dataiku Provides
- Visual flow and interfaces found in Dataiku allow for easy cleaning and enriching of data. The Dataiku flow provides a visual representation of a project’s data pipeline and is the core springboard from which coders and non-coders, data and domain experts alike, can view and analyze their data, add recipes to join and transform datasets and build predictive models.
- Automatic documentation of all of the steps in a recipe as part of the visual flow is a key part of Dataiku’s visual interface. As you gather, group, clean, and enrich your data with just a few clicks, every step is documented for clear and simple tracking of your data preparation processes. This way, everyone stays on the same page. And remember, if you prefer coding over clicking, you’re able to create those code recipes to revisit using languages you’re familiar with such as Python, R, and SQL, developed and edited in your favorite IDE.
- Pre-built connectors in Dataiku help facilitate and maintain seamless integration and upkeep as your organization grows and updates its tech stack. Disparate data sources are no longer a reason to fret when leveraging Dataiku.You can use the pre-built connectors to connect to dozens of leading data sources both in the cloud and on-premises including Amazon S3, Azure Blob Storage, Google Cloud Storage, Snowflake, SQL databases, NoSQL databases, HDFS, and more
- 100 built-in data transformers for common data manipulations like binning, concatenation and strings manipulation, currency and data conversions, geo-enrichment, and reshaping are included in the powerful prepare recipe of Dataiku. Dataiku even evaluates your data’s type and values in order to make relevant function recommendations for your specific data compositions. And again, you can choose your cup of tea, either using a spreadsheet-like expression language or Python for maximum flexibility.
- A wide range of code-based and plugin elements contained in the visual flow allows for added customization and extensibility. You can fit your flow to your specific needs and you don’t have to shy away from the “out-there” problems. Dataiku can tackle more complex data types such as images, natural language, time series data, and even geospatial information.
By utilizing Dataiku at the data preparation stage, you’re checking off the important first steps of analytics and ML success and fortifying a flexible foundation that will give you the footing you need to move beyond the basics.