EnLume's data preparation solution is meticulously crafted to equip data analysts and business users with unparalleled capabilities. Seamlessly explore, structure, cleanse, integrate, and publish data in a truly interactive and visually dynamic manner. Unleash your data's potential with effortless precision.

EnLume’s Data Preparation Advantage

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Data quality

Data quality is the bedrock of effective data analysis and decision-making. We meticulously refine, validate, and enhance your data to ensure accuracy and reliability, enabling you to derive meaningful insights and make informed decisions with confidence.

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Data analysis

Efficiency in data analysis starts with proper preparation. Cleaning, normalization, and meticulous validation are crucial. The quality of input data directly impacts analysis effort and duration. Robust validation ensures accurate interpretations.

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Business value

Data preparation isn't just a step; it's a gateway to business value. Enhance productivity, optimize costs, and unveil improved performance. Experience the transformative impact as data preparation sets the stage for success.

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Accelerated data usage

Cloud-powered data preparation eliminates the need for technical installations and enables seamless collaboration, ensuring faster results.

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Achieve superior scalability

Data preparation scales effortlessly alongside business growth, relieving enterprises from concerns about infrastructure and future evolutions.

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Stay future-proof

Automatic upgrades keep businesses ahead of the innovation curve, without incurring additional costs or delays.

Data quality dimensions addressed by enLume:

1. Accuracy:
Ensuring data sets are free from errors, such as multiple formats, different source fields, or incorrect entries.

2. Completeness:
Verifying the absence of missing data or empty fields in the dataset, including issues arising from synchronization problems.

3. Timeliness:
Assessing the currency and relevance of data to meet the objectives of the analysis, ensuring it is available when needed.

4. Consistency:
Maintaining consistent data formats between systems and identifying and resolving duplicate records.

5. Structure:
Organizing data in a logical and consistent manner, including maintaining relationships between entities and attributes.

6. Clarity:
Eliminating redundancy and minimizing random noise within the data to enhance its overall clarity and usefulness.
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Our competitive edge

Flexible and lightweight ETL/ELT strategies

Our data architecture employs adaptable and efficient Extract, transform, and load (ETL) and extract, load, and transform (ELT)strategies to seamlessly process and stream large volumes of data from diverse sources. This ensures the availability of relevant and accurate data while reducing downtime and network costs.

Data preparation lifecycle

Our integrated data preparation solution handles both internal and external disparate data sources, ensuring high-quality data readiness for analysis. Our team of certified data science professionals delivers tailored solutions to address your specific business challenges.

Interactive and engaging

Data process and management system that integrates, unifies, and standardizes complex data from various sources, enabling the identification of trends, patterns, and relationships through visually appealing and interactive representations.

Predictive and prescriptive analytics

Leverage extensive data science capabilities, quantify the impact of future decisions, offering insights and guidance on possible outcomes before the decisions are implemented. This empowers informed decision-making and proactive planning.

How We Solve It For You

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People

  • Certified resources with expertise on data science
  • Strong professional consulting team
  • Agnostic to resource competencies in database & data analysis
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Process

  • Repetitive tasks automated by a click
  • Efficient tracking of changes and data provenance
  • Reduces data discovery and preparation time
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Technology

  • Integrated solution to make quality data ready for analysis
  • Joint solution from Trifacta and EnLume facilitates easy exploration and discovery to scale
  • Solution running on Amazon Web Services (AWS) to streamline machine learning applications
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Discover

Gain a deep understanding of all data sources, analyzing their structures to align with defined data analytics objectives, even when dealing with disparate data sources.

Data Normalization

Normalize the data by removing redundancies and transforming it into usable formats, ensuring integrity across different units, scales, formatting, segmentation, clustering, etc.

Data Cleaning

Identify and rectify errors and issues related to data quality, such as incompleteness, inaccuracy, inconsistency, outliers, duplicates, etc., while preserving overall data integrity.

Data Integration

Integrate relevant data sets from both internal and external sources to enable faster and comprehensive analysis, consolidating data for enhanced insights.

Data Publishing

Validate and prepare the output dataset for intended analysis, ensuring it is refreshed and available in real-time or batches for machine learning applications and web-scale data processing.

Technology Stack We Use

Source

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Ingestion

    Batch
    • tect_logoAirbyte
    • tect_logoFivetran
    • tect_logoSinger
    • tect_logoStitch
    Streaming
    • tect_logoDataflow
    • tect_logoEvent Hubs
    • tect_logoKafka
    • tect_logoAmazon Kinesis
    CDC
    • tect_logoKafka

    Orchestration

    • tect_logoAirflow
    • tect_logoDagster
    • tect_logoPrefect

    Warehouse/Lake

      Warehouse
      • tect_logoAzure Synapse Analytics
      • tect_logoGoogle Big Query
      • tect_logoDatabricks
      • tect_logoAmazon Redshift
      • tect_logoSnowflake
      Lakes
      • tect_logoAmazon S3
      • tect_logoDatabricks
      • tect_logoGoogle Cloud
      • tect_logoHadoop
      Transformation
      • tect_logodbt
      • tect_logodremio
      • tect_logoPython
      • tect_logoApache Spark

      Downstream

        Analytics & BI
        • tect_logoLooker
        • tect_logoSigma
        • tect_logoTableau
        Operations
        • tect_logoCensus
        • tect_logoHightouch
        • tect_logoRetool
        Data Science
        • tect_logoData Robot
        • tect_logoH2O
        • tect_logoAmazon SageMaker

        Data Monitoring & Management

          Data Quality
          • tect_logoData Fold
          • tect_logoGreat Expectations
          • tect_logoMonte Carlo
          • tect_logoSoda
          Oberservability
          • tect_logoAccel Data
          • tect_logoData Band
          • tect_logoMonte Carlo
          • tect_logoSoda
          Data Catalog
          • tect_logoAmundsen
          • tect_logoAtlan
          • tect_logoStemma
          Security & Governance
          • tect_logoAtlan
          • tect_logoDataddo
          • tect_logoOkera
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