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24/7 Managed Support|
YAKKAY Technologies - AI and Automation Solutions
ADLS Gen2 Consulting

Azure Data Lake Storage Consulting Services Designed to Scale

Organize your cloud data silos into a high-performance analytics machine.

We design, build, and optimize ADLS Gen2 data lakes. Structure multi-stage directories, configure Active Directory security ACLs, deploy Delta Lake, and accelerate analytics while cutting storage bills.

Lake Architecture

What You Get With Our Data Lake Architecture

We construct secure, high-performance data lakes that integrate smoothly into Microsoft Synapse & Databricks.

Optimized File Formats

Auto-convert messy source documents into Apache Parquet or Delta Lake format to minimize compute load and storage size.

Hierarchical Namespaces

Replace heavy emulation layers with real directory indexes, yielding massive speed boosts on query renames and partition lookups.

Intelligent Ingestion Orchestration

Schedule incremental loads using Azure Data Factory, only extracting files modified since the last capture.

Only the best work – driven by AI trained agents

0.0%Data availability SLA
0x-10xFaster analytics queries
0%Average storage cost savings
0,000+Hours saved on manual pipeline fixes
Use Case 1

Data Warehouse Offloading

Move high-volume historical and raw files from costly relational database appliances into a high-throughput Azure Data Lake layer. Run Synapse SQL Serverless directly on parquet/delta files to reduce database compute licensing costs by up to 70%.

  • Serverless query compute over files
  • Saves up to 70% in appliance license fees
  • Retains 100% analytical schema structure
Data Warehouse Offloading
Cost Optimization

Cloud Database & Server Infrastructure

Use Case 2

Real-Time Ingestion Streams

Ingest telemetry, IoT signals, weblogs, and sensor data continuously. Leverage Event Hubs combined with Azure Databricks structured streaming to deliver analytics and alerts within seconds.

  • Sub-second file mapping
  • Bronze -> Silver -> Gold automated pipelines
  • Schema validation at ingest point
Real-Time Ingestion Streams
Data Pipelines

Continuous Event Telemetry Routing

Use Case 3

Dynamic Metadata & Governance

Expose clean, queryable gold tables to business units. Integrate direct connection channels for Power BI dashboards, Synapse workspace SQL, and ML modeling notebooks.

  • Microsoft Purview column lineage logs
  • PII automated mask tags
  • Granular folder permissions
Self-Service Analytics & BI
Enterprise BI

Interactive Metrics & Dashboards

Only the best work – driven by AI trained agents

Our Azure Data Lake
Engineering Services

We provide end-to-end consulting, construction, and migration services to configure a secure and highly scalable storage hub.

1

Azure Data Lake Architecture Strategy

We analyze your enterprise pipelines, data volume, and analytic requirements to draft a blueprint for a secure, performant, and cost-optimized ADLS Gen2 data lake structure.

2

Hierarchical Namespace Partitioning

We configure folders, paths, and partition layouts to optimize parallel file reads. Ensure your Spark, SQL serverless, or Databricks runs run at peak efficiency with zero waste.

3

Lakehouse & Delta Lake Integration

Convert standard CSV/JSON folders into Delta layers supporting ACID properties, schema validation, history timeline logging, and optimized parquet layout sizes.

4

Modern ETL/ELT Pipeline Development

Deploy batch and micro-batch data pipelines using Azure Data Factory, Synapse, and Databricks. Automate data flow from cloud and on-premises environments.

5

Active Directory (Entra ID) & ACL Setup

Map database roles to Microsoft Entra security groups and apply POSIX directory-level ACL permissions. Restrict access to PII and finance folders down to the file level.

6

Automated Lifecycle & Storage Tiering

Build lifecycle policies that transparently transition historical datasets from Hot storage to Cool or Archive storage tiers, saving storage bills automatically.

7

Microsoft Purview Catalog Setup

Establish automated data asset discovery scanners, catalog your fields, map columns pipelines lineage, and maintain clean audit records for security compliance.

8

Legacy-to-Cloud Lake Migration

Seamlessly transfer on-premises Hadoop files, local storage networks, or other cloud buckets (AWS S3, Google GCS) into ADLS Gen2 without business interruptions.

9

Self-Service Business Intelligence Setup

Expose clean, queryable gold tables to business units. Integrate direct connection channels for Power BI dashboards, Synapse workspace SQL, and ML modeling notebooks.

Scale operations

Demo Flow: Automated Ingestion & Zone Separation

Experience the performance of multi-stage storage zones. See how we automate incoming files ingestion, standardise structural schemas, write clean Delta folders, and feed real-time reporting dashboards.

Schema Enforcement
ACID Transactions
POSIX Directory Security
Automated Tiering

powerful features

Enterprise-Grade Security & Scale

Designed to support demanding corporate analytics requirements, ensuring zero-trust isolation and infinite scalability.

Enterprise Grade Scalability

Architected on Azure's massive storage infrastructure, supporting petabyte-scale storage, high throughput, and 11-nines of data durability.

  • Hierarchical Namespace directory system
  • Geo-redundant storage options (GRS/RA-GRS)
  • Automated lifecycle management
  • POSIX-compliant file manipulation

Multi-Zone Pipelines

Maintain separate data stages for raw files, standardized records, and curated reporting datasets, preventing logic pollution.

  • Bronze (Raw Landing) zone
  • Silver (Cleaned Delta) zone
  • Gold (Business Curated) zone
  • Audit & Lineage trails

Robust Security & Isolation

Protect critical enterprise datasets with Active Directory security principles, private endpoints, network firewalls, and detailed logs.

  • Granular folder and file ACLs
  • VNet service endpoints & private links
  • Customer-managed encryption keys
  • Detailed query audit trials

Unified Governance Catalog

Catalog all lake tables, audit access controls, track columns lineage, and categorize data classes by integrating Microsoft Purview.

  • Automated asset scanning
  • Column-level lineage visualization
  • PII classification mapping
  • Data owner dashboards

System & Platform Integrations

Connect your entire analytical ecosystem into a unified cloud storage framework.

System Name
Connection
Integration
Azure Data Factory
Active
Azure Databricks
Active
Synapse Serverless
Active
Microsoft Purview
Active
Power BI
Active

Azure Analytics Services Status

100%
ADLS Storage Layer
Operational
99.98%
Ingestion Pipelines
Operational
99.95%
Databricks Workspace
Operational
99.99%
Purview Catalog
Operational

100% Automated. 100% Reliable.
100% Compliant.

Our Structured Blueprint to Lake Implementation

We employ standard cloud execution steps to deliver maximum engineering efficiency.

1

Discover & Profile

Audit your business operations, data formats, schemas, security standards, and storage budgets.

2

Architect & Organize

Design the optimal file structures, partition strategies, Azure ACL permissions, and zone policies.

3

Orchestrate & Cleanse

Build ADF pipelines and Databricks scripts to automate raw capture, deduplication, and Delta storage.

4

Govern & Document

Connect catalog scanners, create technical lineages, build dashboards, and complete training handovers.

Architecture Checklist

  • Establish folder zones (Landing, Raw, Cleaned)
  • Setup Microsoft Entra ACL permissions
  • Enforce Parquet file formatting
  • Implement Microsoft Purview scanners

Data Platforms We Orchestrate & Target

Connect workflows, engines, catalogs, and reporting models seamlessly.

Data Factory
Data Factory
Azure Databricks
Azure Databricks
Azure Synapse
Azure Synapse
Power BI
Power BI
Apache Spark
Apache Spark
Microsoft Purview
Microsoft Purview
SQL Server
SQL Server
Apache Kafka
Apache Kafka
Event Hubs
Event Hubs
Python
Python
Delta Lake
Delta Lake
Snowflake
Snowflake

Ready to optimize your cloud storage?

Connect with our data engineering team today.

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FAQ

Frequently Asked Questions

Key concepts about ADLS Gen2 big data architectures.

What is Azure Data Lake Storage (ADLS) Gen2?

ADLS Gen2 is a highly scalable, secure cloud filesystem tailored specifically for big data analytics. Built on top of Azure Blob Storage, it introduces a hierarchical namespace (directories and files) and POSIX-compliant permissions, which greatly speed up analytics computations.

How does Hierarchical Namespace (HNS) help with performance?

Standard cloud blob storage emulates folders using virtual paths, meaning directory renames require reading and rewriting all underlying files. ADLS Gen2's Hierarchical Namespace processes folder renames as simple metadata changes, providing a massive performance boost for Spark, Databricks, and SQL serverless engines.

How is access control and security managed?

Data lake security combines Azure RBAC (for administrative control plane access) and detailed POSIX-style Access Control Lists (ACLs) for granular folder-level and file-level permissions, integrated directly with Microsoft Entra ID (formerly Azure Active Directory) security principles.

What are the Bronze, Silver, and Gold zones?

These form a Lakehouse data organization pattern: Bronze stores the raw ingested data as-is; Silver standardizes, cleans, and deduplicates the records (often as Delta Lake format); and Gold models, joins, and summarizes data for final BI consumption and reporting.

Can ADLS Gen2 help reduce storage costs?

Yes, by utilizing Azure lifecycle management rules. You can automatically configure policies to shift raw landing files or older historical data to cooler tiers (Cool or Archive) after predefined time thresholds, lowering storage fees by up to 90%.

Have more detailed questions?

Get in touch with an Azure Integration Specialist.