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    Divya Pal Singh

    Azure and Business Intelligence Architect with 17+ years of experience delivering cloud data and analytics solutions. Focus areas include Azure data platforms, ETL and ELT architecture, and enterprise BI on Microsoft Azure.

    • Home
    • Divya Pal Singh
    Four-step framework shown in sequence: organisational readiness covering who owns which data, then architecture, then governance baselines, then operational standards, with an arrow marking step one as where the framework starts and step two as where most assessments start.
    Data strategy

    A data platform assessment that starts in the wrong place

    September 1, 2026 Divya Pal Singh No comments yet

    A data platform assessment usually starts with architecture. Microsoft’s own first step is ownership, and assessments that skip it produce designs nobody owns.

    Timeline showing a Purview auto-labelling policy activating itself: policy created automatically, simulation runs labelling nothing, seven days pass unedited, then the policy goes live and labels for real, under the heading that what someone has to do for this to happen is nothing.
    Data governance

    Sensitivity labels rollout: your tenant may have started without you

    August 27, 2026 Divya Pal Singh No comments yet

    A sensitivity labels rollout may already be running in your tenant. Default labels arrive on their own, and one policy switches itself on after seven days.

    Before and after comparison of one timestamp column: a Synapse datetimeoffset value showing 2026-03-15 23:45:12.1234567 +05:30 with the trailing digit and time zone offset highlighted, and the migrated Fabric datetime2 value showing 2026-03-15 23:45:12.123456 without them.
    Microsoft Fabric

    Synapse to Fabric migration: what does not move

    August 20, 2026 Divya Pal Singh No comments yet

    A Synapse to Fabric migration moves your schema, not your semantics. The type mappings, the objects the assistant skips, and where data quietly changes.

    The four Fabric throttling stages from overage protection through interactive delay and rejection to background rejection
    Microsoft Fabric

    Fabric capacity planning: what to read before you scale

    August 13, 2026 Divya Pal Singh No comments yet

    Fabric capacity planning starts with the metrics app, not the purchase order. What to read before scaling up, and why doubling the SKU is rarely the fix.

    Fabric workspace items with a Git status column, two marked unsupported
    Microsoft Fabric

    Fabric Git integration: what actually syncs, and where the gap shows up

    August 5, 2026 Divya Pal Singh No comments yet

    Fabric Git integration versions your workspace, but not every item. What syncs, where the gap is flagged, and why nobody looks at the column that shows it.

    Primary and paired Microsoft Fabric regions: OneLake data replicates while workspaces, pipelines and semantic models do not
    Microsoft Fabric

    Microsoft Fabric disaster recovery: what is and is not replicated

    July 31, 2026 Divya Pal Singh No comments yet

    Microsoft Fabric has built-in disaster recovery, and that sentence has given a lot of architecture teams false comfort. The capability is real. What it protects is considerably narrower than most teams assume, and the gap between “DR is enabled” and “we can actually recover” is where the risk lives. This article sets out exactly what […]

    A data pipeline fanning out from one source into parallel processing stages and back to a single sink
    Azure

    Azure Data Factory at scale

    March 10, 2026 Divya Pal Singh No comments yet

    Azure Data Factory (ADF) is Microsoft’s cloud-native ETL/ELT service, but scaling from 10 to 1,000+ pipelines requires architectural patterns that most…

    Medallion architecture layers on OneLake: bronze raw, silver conformed and gold served
    Microsoft Fabric

    Enterprise data lakehouse on Microsoft Fabric

    January 30, 2026 Divya Pal Singh No comments yet

    Microsoft Fabric represents the most significant shift in enterprise data architecture since cloud data warehouses.

    On-premises server racks migrating to Azure VMware Solution
    Azure

    Enterprise Azure VMware solution

    January 23, 2026 Divya Pal Singh No comments yet

    This framework represents a synthesis of 50+ enterprise Azure VMware Solution (AVS) deployments, distilling production lessons into prescriptive technical…

    A governed compute cluster with some objects granted and others restricted
    Azure

    Databricks on Azure: enterprise lakehouse architecture

    November 19, 2025 Divya Pal Singh No comments yet

    The modern data stack has converged on a single architectural truth: the lakehouse.

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    Categories

    • Azure (7)
    • Copilot & AI (4)
    • Data governance (2)
    • Data strategy (1)
    • Dynamics 365 (4)
    • Microsoft Fabric (7)
    • Power BI (1)
    • Power Platform (5)

    Recent posts

    • Four published Business Central limits shown as cards: 300 companies per environment, 3 TB of data, 6,000 OData requests per user, and 10 concurrent background sessions highlighted as the ceiling that binds first
      Business Central vs Finance and Operations
    • Two panels answering which Power Platform projects need a baseline: fast-track for personal helpers under five developer days with no external dependencies, where adoption count is enough, and a hard gate for 50 or more users, premium licensing or auditable processes, requiring cycle time, error rate and labour hours before the sprint.
      Power Apps ROI: the number you cannot recover
    • Decision diagram from the question what do we do if this does not arrive, branching to two answers: nothing, meaning it is an event for Event Grid or Event Hubs, and reconcile, raise a ticket or re-send, meaning it is a command for Service Bus.
      Azure messaging services: the choice is command or event

    Tags

    Azure analytics Azure Databricks Azure Data Factory Azure VMware Solution Microsoft Fabric Microsoft Purview Power BI
    Veratas

    Veratas empowers businesses with advanced analytics and tailored software solutions in the Microsoft ecosystem. From Dynamics 365 to Microsoft Fabric, we help organizations unlock insights, optimize performance, and drive growth.

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