Data Engineering & Analytics:

Data Engineering & Analytics:

About Data Engineering & Analytics

Unlock the full potential of your data with Adroit’s bespoke solutions. Our team of experts will work with you to carry out an in-depth data discovery process, identify your current and future business needs, and develop a tailored solution that meets your unique requirements. Whether you need a data lake or a data warehouse, we’ll help you build a secure and compliant data platform with future scope and scale built in from day one.

We understand that having a clear understanding of your goals is essential to success. That’s why we take the time to identify the Key Performance Indicators (KPIs) that matter most to your organisation and develop dashboards that provide valuable insights at different levels, from Geographical to Territory. We also understand that the audience at different levels within your organisation will want a different level of information and flavour to their insights, so we build from the ground up from your field teams up to C-suite and board level. 

Data security is paramount, and our team has the expertise to ensure that your data is fully protected. We’ll work with you to identify roles and responsibilities and implement access restrictions to prevent unauthorised access or develop a transparent approach that allows all users to access all data.

How it Works

As your trusted partner in your data storytelling journey, Adroit is committed to maximising the value of your data for your organisation. Even helping you discover data which you did not know existed. We provide the support and guidance you need to make informed decisions about your data and help you unlock its full potential in helping manage your business now but also plan for the challenge in the future.

Data Audit

At Adroit, we understand the importance of compliance with industry standards, best practices, and regulatory requirements. That’s why we offer a comprehensive data audit service to review your current data infrastructure and processes. Our team will identify potential vulnerabilities, inefficiencies, or non-compliance issues within your data ecosystem and provide recommendations for improvement.

During the audit, our Data Engineers will identify your current data sources and build a roadmap of recommendations and improvements based on data derived from the following key sources:

  • Transactional data: Data generated by business transactions, such as sales records, financial transactions, and customer interactions.
  • Streaming data: Real-time data generated continuously, such as sensor data, log data, or social media data.
  • Web data: Data collected from web pages, such as web scraping or data from APIs.
  • External data: Data collected from external sources, such as government data, weather data, or financial data.
  • Legacy data: Data stored in older systems or formats, such as mainframe data or legacy databases (e.g. previous CRM tool)
  • Human-generated data: Data generated by humans, such as survey responses, customer feedback, or user-generated content.
  • Meta Data: Any data that underpins the data sources above (e.g. created date, last update date, created by – we consider this the metadata of your data sources)
  • Data Quality: We understand that having multiple data sources is great, but it’s equally important to ensure the completeness and accuracy of your data sets. That’s why we can build schemas to show the quality of your data and highlight any potential blind spots, such as missing data, incomplete data, or unreliable data.

Our data audit service is designed to help you understand your data ecosystem better, identify areas for improvement, and ensure compliance with industry standards and regulatory requirements. Trust Adroit to help you unlock the full potential of your data.

Visualisation & Reporting

At Adroit, our Data Engineers use a range of tools to optimise and enhance your business’s data quality and efficiency through analysis and automation. These tools provide valuable insights into complex data and can improve the visualisation and reporting of information.

Modelling: This is a crucial aspect of the process, involving the creation of data models to feed your dashboards and reports. Data modelling helps organise and structure data, improve data quality, design databases, support decision-making, and streamline data integration. By identifying these requirements, we can help your organisation better understand and utilise your data by creating a visual representation of data relationships.

Visualisation: We work with you to determine the most important views, trends and metrics for your data story. Do you need a snapshot in time or the ability to compare historical time frames? Our modelling work enables us to visualise your data in the best possible way.

Through detailed dashboards and reports, we can identify patterns, trends, and outliers in data, and communicate insights in a clear and concise manner. Visual representation makes it easier to understand complex data, leading to more informed decision-making and making data more accessible to a wider audience. Additionally, data visualisation can be used to monitor performance and metrics, helping to identify and track areas for improvement and progress within your estate.
Metadata: This is a vital part of the data visualisation process as it provides a structured and organised way to describe and manage data. Providing context, meaning, and relationships between different data elements, making it easier to understand and use data. Metadata can include information about data sources, types, quality, lineage and usage, among other things. This information helps us to improve the accuracy and consistency of our data visualisation, and can also help support data governance, integration, and analytics efforts. Metadata also helps us to simplify data management tasks by providing a common language and framework for describing data across different systems and applications. Overall, metadata is a critical component of effective data management and analysis in the Adroit Data Audit Process.

Big Data

Adroit can help your business harness the power of Big Data and gain valuable insights from vast amounts of structured and unstructured data. With our expertise in handling large and complex data sets, we can design, build and manage Big Data solutions that can process, store, and analyse data at scale.

Data ingestion: We can help you collect, extract, and load large volumes of data from various sources into a centralised data store or a distributed data processing framework.


Data processing: We can use tools and techniques such as Hadoop, Spark, and Kafka to process large volumes of data and transform it into usable insights and analytics.


Data storage: We can design and implement scalable and resilient data storage solutions that can store and manage petabytes of data using technologies such as HDFS, S3, and Azure Data Lake.


Data analytics: We can use advanced analytics techniques such as machine learning, data mining, and predictive modelling to extract insights and patterns from Big Data.


Data visualisation: We can create customised dashboards and reports to help visualise and communicate insights from Big Data to different stakeholders across your organisation.


Data security: We can ensure that your Big Data solutions are secure, compliant, and protected against potential threats and vulnerabilities.

Adroit’s Big Data Service offers a comprehensive solution to manage and analyse vast amounts of data. Our team will collaborate with you to recognise your specific needs and deliver tailored recommendations to optimise your data infrastructure. We use state-of-the-art technology and tools to assist you in storing, managing, and analysing your data, providing valuable insights and supporting informed decision-making.

Data Types

Understanding the different types of data is crucial for businesses looking to extract insights and make informed decisions. Unstructured data refers to data that is not managed in a transactional system and can include media and entertainment data, surveillance data, geo-spatial data, audio, and weather data, among others. Document collections such as invoices, records, emails, and productivity applications also fall under unstructured data. The Internet of Things (IoT) generates sensor data and ticker data, while machine learning and artificial intelligence (AI) produce analytics data.

On the other hand, structured data is a collection of records or transactions in a database environment, such as rows in a table of a SQL database. Although there is no preference between structured and unstructured data, the latter is often more abundant. Businesses must use tools to access both structured and unstructured data to obtain valuable insights.

Data integration plays a crucial role in consolidating structured and unstructured data. It involves combining data from various sources to create a unified view of the information, making it easier to analyse and interpret. This process ensures that data is consistent, accurate, and complete, allowing businesses to gain a comprehensive understanding of their operations. With our expertise in data integration, Adroit can help you create a single source of truth for your business data, leading to more informed decision-making.

Get in touch

If you have any further questions or are ready to take the next step and begin working with Data Engineering & Analytics services, please get in touch

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