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    Process layer

    assimil8 > Modern tech stack

    This is where your data is transformed, modelled, and captured. We use tools such as DBT, Apache Spark, and Bundle Capture to ensure that your data is processed efficiently and accurately. 

    

    Our partnerships with these vendors also enable us to provide our clients with the latest and most effective tools for processing their data, meaning that you are always at the forefront of innovation.



    What is the process layer?

    The process layer is responsible for transforming, modelling, and capturing data that has been collected and stored in the storage layer. The goal of the process layer is to make the data ready for analysis and reporting by cleaning, enriching, and structuring it in the appropriate way.


    There are three main processes within the layer, they are modelling, transformation, and capture. 

    The three process layers


    Data modelling is the process of creating a visual representation of data and its relationships to other data elements. There are several different types of data models, all of which have their own benefits. They are;


    Conceptual model: A high-level representation of data designed to provide a broad understanding of the data elements and their relationships. 


    Logical model: A more detailed representation of data that focuses on the relationships between data elements. 


    Physical model: A representation of data that takes into account the physical storage of the data in databases or other data storage technologies.


    Data modelling is used in a variety of industries and applications, to help them make key decisions based on their data. For example;


    • In healthcare, it can be used to create models of patient data to improve patient outcomes and reduce costs. 

    • In finance, it can be used to create models of financial data to make investment decisions and assess risk. 

    • In retail, it’s used to create models of customer behaviour to improve marketing and sales strategies. 
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    The Transformation Process

    The transformation process involves manipulating, cleaning and enriching your data to make it more useful for analysis and decision-making. It involves the application of various operations to the data, such as filtering, sorting, aggregating, joining, and transforming.


    One of the key benefits is that it improves the quality and accuracy of your data. By cleaning and enriching the data, it can eliminate duplicates, fill in missing values, and correct errors, making the data more reliable and trustworthy.


    Finally, the capture process involves the capture and extraction of from multiple sources, including databases, files, and APIs, before transferring the data and storing it in a centralised location. 


    One of the key benefits of the capture process is that it allows your business to automate data collection and reduce the risk of errors. By automating the capture process, you can reduce the time and effort required to collect and store data, and eliminate the risk of errors associated with manual data entry.

    There's a tool for that

    One of the key benefits of the capture process is that it allows your business to automate data collection and reduce the risk of errors. By automating the capture process, you can reduce the time and effort required to collect and store data, and eliminate the risk of errors associated with manual data entry.


    Our process layer is built on a number of technologies, including Apache Spark, DBT, and Bundle Capture. But what are their benefits? 


    Apache Spark is an open-source framework for distributed processing of large data sets.


    DBT (data build tool) is a popular open-source tool for managing the transformation of data, and;


    Bundle Capture is a data extraction and transformation tool that can help your business capture data from multiple sources and prepare it for analysis.

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    Identify patterns and insights

    One of the main benefits of the process layer is how it prepares your data for detailed analysis through the use of transformation. Making it easier to structure the data to help identify patterns, trends and insights. 


    In addition, the process layer can help your business identify key areas where your data is lacking or incomplete. This will give you the opportunity to extract more data or to cleanse the data to make it more accurate. 


    Award winning data

    insights and analytics

    We work with customers to help them to become data-driven organisations, driving commercial growth and adding value. If you would like to know how assimil8 can add value to your business, click the button below to get a personalised quote.

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