Data Intelligence

Data Mapping

Data mapping is a fundamental aspect of building data intelligence within an organisation, enabling businesses to understand, organise, and leverage their data assets effectively.

Data mapping involves the process of identifying and documenting data sources, fields, attributes, and relationships to create a comprehensive view of the organisation’s data landscape. By mapping data flows and dependencies, organisations can gain insights into data lineage, quality, and usage, facilitating informed decision-making and driving strategic initiatives.

We help businesses assess their current data landscape, identify data sources and dependencies, and develop a structured framework for managing and leveraging data assets. Through a systematic approach to data discovery, documentation, and analysis, we help organisations to unlock the value of their data and harness it to achieve business objectives and drive competitive advantage.

Initial Consultation

We start by engaging in an initial consultation with key stakeholders to understand the organisation's data management goals, challenges, and priorities. This helps us tailor the data mapping process to address specific business needs and objectives.

Data Discovery

We conduct a comprehensive inventory of data sources within the organisation, including databases, applications, files, and external sources. This involves identifying data owners, custodians, and stakeholders responsible for managing and maintaining data assets.

Data Profiling

We analyse the structure, content, and quality of data across different sources to assess data consistency, accuracy, and completeness. This includes profiling data fields, identifying anomalies or discrepancies, and documenting data characteristics and patterns.

Data Lineage

We trace the flow of data across systems and processes to understand how data moves and transforms within the organisation. This involves mapping data flows, transformations, and touchpoints to visualise data lineage and dependencies.

Data Governance

We evaluate the organisation's data governance practices, policies, and controls to ensure data integrity, privacy, and compliance. This includes assessing data access controls, data retention policies, and data stewardship responsibilities to mitigate risks and ensure regulatory compliance.

Data Documentation

We document data mappings, definitions, and metadata attributes to create a centralised repository of data knowledge. This includes developing data dictionaries, data lineage diagrams, and data flow diagrams to facilitate communication and collaboration across teams.

Data Quality Assessment

We assess the quality of data across different dimensions, such as accuracy, completeness, consistency, and timeliness. This involves profiling data quality metrics, identifying data anomalies or errors, and implementing data cleansing or enrichment processes to improve data quality.

Data Integration

We identify opportunities for integrating data across disparate sources to create a unified view of the organisation's data assets. This includes defining data integration requirements, mapping data transformations, and selecting integration technologies and tools to streamline data exchange and consolidation.

Data Security and Privacy

We evaluate data security and privacy measures to protect sensitive information and ensure compliance with data protection regulations. This includes implementing data encryption, access controls, and data masking techniques to safeguard data confidentiality and integrity.

Data Usage and Analysis

We analyse data usage patterns and user requirements to identify opportunities for leveraging data assets for business insights and decision-making. This involves defining data analytics use cases, developing data models, and implementing analytics solutions to derive actionable insights from data.

Data Strategy and Roadmap

Based on the assessment findings, we collaborate with stakeholders to develop a data strategy and roadmap for achieving data intelligence objectives. This includes prioritising data initiatives, defining milestones, and establishing governance mechanisms to drive data-driven transformation and innovation.

By conducting data discovery, profiling, and lineage analysis, we help organisations gain insights into data quality, usage, and dependencies, facilitating informed decision-making and driving strategic initiatives.

 

The benefits of doing:

Enhanced Data Understanding: Through data discovery and documentation, organisations gain a comprehensive understanding of their data landscape, including sources, attributes, and relationships, enabling informed decision-making and strategic planning.

Improved Data Quality: Data profiling and quality assessment enable organisations to identify and address data inconsistencies, inaccuracies, and anomalies, ensuring higher data quality and reliability for business analysis and decision-making.

Increased Data Governance: Data mapping facilitates the establishment of data governance practices, policies, and controls, ensuring data integrity, privacy, and compliance with regulatory requirements, thereby mitigating risks and enhancing trust in data assets.

Optimised Data Usage: Analysis of data lineage and usage patterns helps organisations identify opportunities for leveraging data assets to derive actionable insights, drive innovation, and achieve business objectives, resulting in improved efficiency and competitiveness.

Strategic Decision-Making: By providing a structured framework for managing and leveraging data assets, data mapping empowers organisations to make data-driven decisions, formulate strategic initiatives, and drive business growth and competitive advantage.

The consequences of not:

Data Inaccuracy and Inconsistency: Without proper data mapping, organisations may struggle with data inaccuracies, inconsistencies, and discrepancies, leading to erroneous insights, flawed decisions, and decreased confidence in data-driven initiatives.

Poor Data Governance: Lack of data mapping hampers the establishment of effective data governance practices, exposing organisations to risks related to data integrity, privacy breaches, and non-compliance with regulatory requirements, resulting in reputational damage and legal liabilities.

Limited Data Utilisation: In the absence of data mapping, organisations may underutilise their data assets, missing opportunities to derive actionable insights, drive innovation, and gain competitive advantage, leading to inefficiencies and missed business opportunities.

Inefficient Decision-Making: Without a clear understanding of data sources, attributes, and relationships, decision-makers may rely on inaccurate or incomplete information, leading to suboptimal decisions, wasted resources, and missed business opportunities.

Lack of Strategic Direction: Neglecting data mapping deprives organisations of a strategic roadmap for leveraging data assets effectively, hindering their ability to align data initiatives with business objectives, drive innovation, and achieve sustainable growth and competitiveness.

About Us

Dual Impact

With a shared journey spanning over two decades, we launched our first ventures from the same shared offices. Throughout the years, we’ve witnessed the highs and lows, and the growth of our respective businesses. We’ve provided unwavering support to one another, celebrating victories and overcoming challenges, which has not only made us successful business partners but has also forged a strong and enduring friendship.

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Both been in business
for over 25+ years

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Both built and owned
7-figure businesses

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Collectively delivered
hundreds of projects