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DataHub 360

Data Hub 360 is built on Google Cloud Storage (GCS) and provides a secure, flexible and scalable cloud infrastructure for managing, storing and making all of the organization's data sources accessible in one central place.

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DataHub 360

The business story

  1. 1

    The Business Challenge

    Many organizations manage data across separate systems that are not synchronized with one another, which leads to:

    • Delayed decision-making due to information scattered across systems, departments and sources.
    • Poorly organized data that makes it hard to identify risks, bottlenecks and anomalies in real time.
    • Business processes affected by partial, outdated or inconsistent information.
    • Managers struggling to obtain a complete, up-to-date picture of the organization's activity.
    • Significant time spent collecting, cross-checking and validating data instead of advancing business tasks.
    • Impaired collaboration between organizational units working off different data sources.
  2. 2

    The Solution

    An organizational Data Hub platform was established, consolidating information from different systems and sources into a unified working environment. The solution includes:

    • Ingestion of data from organizational systems and multiple data sources.
    • A Data Lake for managing structured, semi-structured and unstructured data.
    • A Data Warehouse and Analytical Data Store for BI and analytics.
    • An organizational data catalog and metadata.
    • Data cleansing, quality control and version management.
    • Integration between geographic, alphanumeric and document-based information.
    • Dashboards and BI views for decision-makers.
    • Digital Twin and Geo Digital Twin capabilities for advanced spatial information.
    • Permissions, data security and identity management mechanisms.
  3. 3

    The Business Value

    • A single organizational source of truth
      Unifying all data sources into a central platform that enables work based on consistent, up-to-date and reliable data.
    • Data-driven decision-making
      Providing processed information, reports and dashboards that help managers understand trends, identify risks and prioritize actions.
    • Breaking down silos between units and organizations
      Connecting data sources, processes and stakeholders into a single working environment that improves collaboration and coordination.
    • Identifying bottlenecks and obstacles
      The ability to analyze cross-cutting data and detect obstacles, process dependencies and impacts on projects and tasks early.
    • Accelerating processes and reducing manual work
      Reducing the time and resources invested in collecting, cleansing and cross-checking data from multiple systems.
    • Infrastructure for growth, innovation and AI
      Creating a high-quality data foundation that enables advanced analytics, forecasting, Digital Twin and artificial-intelligence capabilities in the future.
  4. 4

    Estimated deployment timeline

    ~4 Months to full deployment
    1. 1

      Proof of concept (POC, optional)

      Capability proof and connection of initial data sources

      ~ 2 weeks
    2. 2

      Kick-off

      Defining business goals and data sources

      ~ 1 week
    3. 3

      Characterization

      Mapping needs, processes and the data model

      ~ 2-4 weeks
    4. 4

      Build & integration

      Connecting systems, building the platform and dashboards, and testing

      ~ 2-3 months (depends on scope)
    5. 5

      Go-live

      Training, onboarding and expanding usage

      ~ 1 week
  5. 5

    Supporting products

    Products implemented as part of this project

    Enterprise Data Catalog

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