B1 MDI: AI SOLUTION FOR AUTOMATED DATA NORMALIZATION
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B1 MDI (Master Data Intelligence) is an AI-powered solution developed by BaOne to automate the normalization of master data. It tackles common data issues such as duplicates, inaccurate records, incomplete information, as well as challenges with integrating data from different systems. With B1 MDI, you can organize your data, cut down on costs and improve your processes.
From an IT perspective, master data refers to the collection of directories and classifiers used across information systems to support business processes—and the documentation that governs how these resources are maintained.

Key directories

  • Inventory purchases
  • Manufactured products
  • Fixed assets
  • Services/work
  • Contracts
  • Customers
  • Suppliers/manufacturers
  • Real estate
  • Equipment
  • HR management
Master data is essential for solving key business tasks. In fact, errors in master data are often a leading cause of ERP project failures.

What problems arise from unnormalized data?

  • Incomplete directories, hindering fast, well-informed operational and managerial decision-making
  • Poor data quality, including duplicates, incorrect entries and non-unique records
  • Ineffective or missing search tools, making it harder to find the right information
  • Inconsistencies in master data across systems, resulting in informational discrepancies
  • Difficulty or inability to consolidate information from multiple systems
  • Regulatory risks, such as fines for incorrect classification under national Commodity Nomenclature codes
  • Product duplication due to incorrect labeling
  • Excessive labor costs associated with manually correcting data issues
  • Stock overages when system data does not reflect actual inventory levels

To address these challenges, data normalization is crucial. It involves streamlining diverse business data into well-organized, stable structures. This approach reduces data redundancy and makes it easier to quickly search and access relevant information.

Key features and capabilities of B1 MDI

Process automation
  • Data cleansing – Removing stop words, fixing typos, handling transliterations, and correcting syntactical and spelling errors
  • Classification – Automatically sorting data into categories and classes using machine learning algorithms
  • Attribute filling – Automatically populating attribute values using various ML models, based on existing directories, and pulling in extra data from global databases
  • Duplicate detection – Automatically identifying duplicates based on key attributes (master data characteristics)
  • Target naming – Generating consistent, standardized product names based on configured rules and classifiers
Analytics & reporting
  • Data profiling – Assessing data quality, focusing on its accuracy, completeness and relevance
  • Normalization progress reports – Creating detailed reports on the status of the data normalization process

Effects and potential benefits of data normalization

  • Reduced labor costs for consolidated reporting (up to 50%)
    Achieved by standardizing data descriptions, eliminating duplicates and processing incomplete data.
  • Lower working capital spend on centralized procurement (savings up to 20%)
    Enabled through consistent product naming and more accurate SKU identification.
  • Reduced inventory holdings and obsolete stock (10%–15%)
    Driven by the removal of inaccurate entries and resolution of mismatches between system data and actual inventory.
  • Faster integration (up to 30%)

    Standardized master data directories and global identifiers significantly simplify integration efforts.
  • Decreased downtime (10%) and increased on-time deliveries (20%)
    Standardized master data directories and global identifiers significantly simplify integration efforts.
  • Lower risk of incorrect payment allocations

    Enabled by cleaner and more reliable customer records.
  • Improved profit and loss reporting

    Resulting from structured, consistent data across multiple systems.
  • Streamlined supply chain


    Achieved through the alignment of legacy and current data, and removal of inaccurate records.

What you get with data normalization

  • Clean, consistent records through deduplication, standardization and processing of incomplete data
  • Easier search and faster matching of similar or related entries
  • Elimination of poorly described items and those that don’t align with updated templates or classifications
  • Well-organized data across systems, enabling smoother, more efficient integration
B1 MDI is a modern solution that brings together AI technologies with deep data management expertise. It helps organizations minimize risks from inaccurate data, accelerate digital transformation and improve overall performance.
Have questions? Talk to an expert today – and see how B1 MDI can work for you!
  • Vitali Baum
    A technology expert with over fifteen years of experience serving international companies.
    Specializes in digital transformation programs across various industries, with a special focus on implementing IT products for retail and e-commerce (both B2B and B2C), oil producers, OFS firms, insurance companies and pensions funds.
    innovations@baone.ae
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