Data Preparation

Identify and eliminate anomalous records from your data sets through machine-learning-based smart techniques and sampling with just a few clicks. Apply these changes to your datasets and export the refined, analysis-ready data for further insights.

Easy Data Preparation Access

Access the Data Preparation feature through two convenient pathways:

  • Access from Data Set List Page
  • Access from Data Sandbox List Page

Whether you're refining datasets for optimal performance or fine-tuning your data we ensure that essential data cleansing tools are right at your fingertips. Be assured of getting prime and potentially powerful data manipulation experience with BDB Data Preparation.

Challenges

Data Quality and Consistency

  • >> Thorough cleansing and transformation of data to address inconsistent formats, missing values, and inaccuracies is often necessary for data readiness in analysis. To get precise, complete, and consistent datasets is often challenging in the data analytics realm.

Complex Data Transformations

  • >> Data preparation frequently involves intricate transformations and calculations. Managing these transformations, particularly for large and diverse datasets, can be challenging.

Optimizing Data Preparation Pipelines

  • >> Crafting efficient and optimized data preparation pipelines that minimize computational resources and time is a common challenge, especially when dealing with complex transformations.

Solutions

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Detect and Resolve Missing Values

  • Identify and Address Missing Values : Use the Profile Info and Quality Bar to identify missing values and replace them with appropriate defaults or values from the neighbouring columns (above or below). This ensures effective data handling while maintaining data consistency for your analysis.
  • Handle Inconsistent Data Formats :  Employ the various sets of data cleansing transforms to tackle inconsistent data formats by standardizing text cases, removing special characters, and converting data types to ensure consistency across the dataset.
  • Create a Clear Data Preparation Workflow : Organize your workflow logically by initially addressing missing data, progressing to standardization and transformation, and concluding with validation and aggregation as required. This systematic approach ensures a well-organized and comprehensive data preparation process.
  • Data Preparation Steps :  keep a record of all the Transformations you do to make the data better and more consistent. This is important because it makes it clear what you've done and lets you or others do the same things again in the future, so the data stays good, and everyone can trust it.

Employ Advanced and Intricate Transformations

  • Use Arithmetic and SQL Transformations : BDB Data Preparation offers Arithmetic, SQL, and Expression transforms for advanced data transformations, enabling mathematical operations, text manipulations, and conditional logic to enhance your data.
  • Data Profiling :  Harness the power of the Data Profiling feature for the visual exploration of your data, aiding a deeper understanding of data distribution and pattern recognition.
  • Multiple Steps :  Implement a multi-step strategy by breaking down complex transformations into smaller, manageable operations. Commence with simpler steps and progressively incorporate complexity. This method not only enhances manageability but also provides valuable insights into intermediate outcomes throughout the transformation process.

Simplify Your Workflow

  • Simplify Your Workflow :  Keep your data preparation workflow as simple and straightforward as possible. Remove unnecessary steps, transformations, or duplicate operations that don't contribute to your analysis.
  • Use Extracts : Use BDB Data Preparation as an intermediate step while working with large datasets as it is highly compressed and pre-aggregated to significantly reduce the data processing time.
  • Optimize Calculations :  Carefully use Expression and SQL transformation as the complex calculations and optimize them to enhance the overall efficiency of the analytic workflows.

Features of Data Preparation

A robust data preparation approach becomes an indispensable foundation for deriving meaningful insights and building accurate models in the realm of data analysis and machine learning.

Basic Anomaly Detection

  • Fine-tune your data for analysis, cleanse outliers, or reshape it to fit your needs.
  • Deploy a fundamental anomaly detection algorithm that automatically recognizes anomalies within the dataset upon its upload.

Diverse Range of Data Transformations

  • Access an extensive range of over 100 data transformations, empowering users to seamlessly conduct both basic and advanced data cleansing operations.
  • Explore a diverse range of transformations designed to refine and optimize your dataset, ensuring a comprehensive solution for all your data cleansing needs.

Seamless Data Exploration with Dynamic Data Grid Updates

  • Delve effortlessly into your selected dataset with an intuitive Data Grid view.
  • Use a highly responsive interface for efficient data exploration. Enable users to visualize a paginated grid, displaying a sample of the data (e.g., 10,000 rows) for enhanced clarity.
  • The dynamic Data Grid ensures you stay in sync with your dataset's evolution and witness real-time changes getting reflected within it by applying a myriad of transformative actions.
  • Statistical Profile of Data: Generate a statistical profile of the dataset, showcasing key metrics and insights to help users understand the data better.
  • Quality Bar for Data Quality Indication: Display a quality bar indicating the percentage of valid, invalid, and blank rows in the dataset, providing a quick overview of data quality.

  • Experience a new era of efficiency and interactivity in the world of data manipulation.
  • Apply a selective set of transforms using automated functionality such as our AutoPrep feature for instant data transformation.
  • Unleash the power of auto-suggestions to get a tailored list of relevant data transformations, precisely aligned with the selected data type.
  • These smart recommendations streamline data cleaning, allowing you to quickly refine your dataset with pinpoint accuracy.

  • Access a clear list of transforms that have been performed on the current data, ensuring transparency and traceability.
  • The Steps tab empowers users to access, edit, and delete any transformation step at any point in their ongoing data cleansing operation.
  • This flexibility and control ensure that your data processing workflow is efficient and customized to your specific needs.
  • Transforms on Filtered Data: Allow users to apply transformations 6specifically on the filtered subset of the data for targeted operations.

  • Efficiently extract and store your meticulously cleaned, transformed, and analysis-ready data as Data Preparations, ready to be utilized after the application of your desired transformations.
  • Effortlessly export your Data Preparations to both the Data Pipeline and DS Lab modules with a simple click.
  • Unlock the power of streamlined data flow, facilitating advanced data analysis and experimentation with unparalleled ease.

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