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| Feature | Free | Pro 1 Day | Pro Monthly |
| Max. characters processed per file | 30000 | 300000 | 300000 |
| Max. no. of file uploads processed | 3 | 10 | 10 |
| Trusted User Benefits (Bypass reCAPTCHA) | No | Yes | Yes |
Use Sedona Bulk Data Summary and Profile Tool to easily identify correlated values and data statistics in batch or bulk.
Example file upload sample template
-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)
-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)
-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)
Related helpful articles around the web for reference
The Importance of Data Profiling
The quality of your data significantly impacts its effectiveness. Assessments show that only around 3% of data meets quality standards, which leads to substantial financial losses for companies due to inefficient management of data. Healthy data should be easily accessible, understandable, and valuable to users, making data profiling essential for any organization aiming for optimal performance. This article examines data profiling and how it transforms raw data into actionable business insights.
What is Data Profiling?
Data profiling involves analyzing and summarizing data to uncover its quality, integrity, and trends. It helps identify issues such as missing or erroneous values, allowing organizations to leverage insights for strategic advantage. The process includes statistical analysis to determine key metrics and metadata, enabling companies to align their data with business goals.
Benefits of Data Profiling
Poor data can cost businesses up to 30% of their revenue, translating into millions lost in resources and tarnished reputations. Often, this stems from oversight in data collection and management. A robust data profiling tool continuously analyzes and improves data quality, offering several key benefits:
Improved Data Quality
:
Analyzing data helps eliminate duplicates and identify quality issues, influencing business decisions positively.
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Enhanced Predictive Decision-Making:
Data profiling allows organizations to foresee potential problems and outcomes, leading to more informed decision-making.
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Proactive Crisis Management:
Quickly identify and address data issues before they escalate.
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Organized Data Management:
Profiling can trace data back to its source, ensuring compliance with security standards and aligning with business rules.
Types of Data Profiling
Data profiling techniques fall into three primary categories:
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Structure Discovery:
Evaluates data consistency and formatting.
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Content Discovery:
Focuses on ensuring data quality and proper integration.
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Relationship Discovery:
Identifies connections among various datasets.
Real-World Applications of Data Profiling
Companies can struggle to harness the full value of their data without effective profiling. For example:
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Domino’s:
Faced with a surge of data from its AnyWare ordering system, Domino’s implemented data profiling to enhance customer insights and operational efficiency, ultimately boosting sales.
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Office Depot:
Utilizes data profiling to ensure high-quality integrated data across multiple channels, providing a comprehensive view of customer interactions.
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Globe Telecom:
Improved its data quality processes, resulting in enhanced customer insights and significant increases in marketing campaign effectiveness.
The Future of Data Profiling
With the rise of cloud storage and data lakes, the need for effective data profiling is more crucial than ever. Automated data management solutions streamline this process, ensuring data integrity and compliance.
Conclusion
Data profiling is a foundational step in managing data effectively. By employing data profiling tools, organizations can gain a comprehensive view of their datasets, ensuring high quality and facilitating informed decision-making. This ultimately leads to better operational efficiency and reduced costs.
What DME’s Data Profiling Can Offer You
Data Profiling Overview
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Completeness and Uniqueness Analysis
: Identify the number of blank or unfilled values in your dataset and count distinct values.
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Frequency Analysis
: Evaluate how often certain values appear.
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Character Analysis for Strings
: Analyze text data for various characteristics.
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Statistical Analysis for Numbers
: Examine numerical data for statistical insights.
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Pattern Recognition and Data Validation
: Detect patterns and validate data integrity.
Additional Features Included
DME’s data profiling solution provides numerous built-in features for seamless and cost-effective data profiling:
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Bulk Profiling
: Analyze multiple data sources at once.
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Central Repository
: Access all your data profiles in one place.
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On-Demand Profile Generation
: Create data profiles whenever needed.
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Multi-Format Export
: Easily export results in various formats.
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Custom Filters
: Apply personalized views to your data.
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Map Charts
: Visualize address data on maps.
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Version History
: Track changes in data profiles over time.
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Automated Scheduling
: Set up automatic data profile generation.
User Roles Supported
DME’s tool is designed for a wide range of users, including:
- Data Analysts
- Business Users
- IT Professionals
- Novice Users
Comprehensive Data Quality Management Lifecycle
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Import
: Connect and integrate data from various sources.
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Profiling
: Automate data quality checks for immediate reporting.
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Cleansing
: Standardize and transform datasets effectively.
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Matching
: Implement advanced matching algorithms on datasets.
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Deduplication
: Remove duplicate entries to maintain uniqueness.
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Merge & Purge
: Set up rules to optimize data merging and retention.
Data Profiling Tools in Power Query
Enhance your data profiling experience with tools in Power Query, including:
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Column Quality
: Visual indicators show data validity, errors, and emptiness.
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Column Distribution
: Visualize the frequency and distribution of values.
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Column Profile
: Provides comprehensive statistics and insights into your columns.
Note
: Power Query defaults to profiling the first 1,000 rows, but this can be adjusted to analyze the entire dataset.
Key Features of Data Profiling Tools
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Column Quality Indicators
: Evaluate the validity of data across different categories.
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Value Distribution Analysis
: Understand how values are distributed within columns.
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Statistics Overview
: Gain insights into minimum, maximum, and average values.
Dataedo for Enhanced Data Understanding
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Data Dictionary
: Explore sample data to learn about your data assets.
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Top Values Report
: Identify the most frequently occurring values in your database.
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Statistical Insights
: Discover min, max, average, and median values along with their distribution.
Utilize DME’s data profiling capabilities to gain deeper insights, ensure data quality, and make informed decisions.
