Databricks Consulting, Implementation & Migration Services
Kanerika helps enterprises leverage the incredible features of Databricks to enhance their data analytics, governance, and AI ecosystem. Our certified experts design, implement, and optimize Databricks environments that deliver speed, scalability, and insights.
Watch Kanerika Unlock Faster Insights with Databricks
Proven Expertise, Measurable Outcomes
60%
Reduction in infrastructure costs
70%
Shorter ETL
runtime
5x
Faster Data
processing
80%
Improvement in
data accuracy
50%
Faster time to
insights
Comprehensive Suite of Databricks Services
Kanerika delivers end-to-end Databricks consulting, implementation, and migration services. From strategy to deployment and ongoing optimization, we help you every step of the way.
Consulting & Strategy
- Assess your current data landscape and analytics maturity.
- Build a Databricks adoption roadmap with governance and security.
- Define architecture and integration strategies for cloud deployment.
Implementation & Deployment
- Deploy Databricks on Azure, AWS, or Google Cloud with best practices.
- Configure clusters, workspaces, governance, and access controls.
- Integrate Databricks with your data lakes, warehouses, and BI tools.
Data Engineering & Pipeline Development
- Design automated ETL and ELT workflows using Delta Lake.
- Implement medallion architecture with bronze, silver, and gold layers.
- Build streaming and batch pipelines that scale seamlessly.
AI & Machine Learning Implementation
- Build scalable ML pipelines using MLflow and Databricks notebooks.
- Deploy predictive models and AutoML workflows for faster insights.
- Build and deploy production-grade gen AI applications with Mosaic AI.
Data Governance, Security & Compliance
- Implement Unity Catalog for unified data governance and lineage.
- Apply fine-grained, role-based access and permission controls.
- Maintain compliance with the GDPR, HIPAA, and SOC 2 standards.
Managed Services & Continuous Support
- Provide 24×7 monitoring, alerts, and issue resolution.
- Manage platform updates, patches, and version upgrades.
- Deliver proactive performance and cost optimization.
MIGRATION SOLUTIONS
We specialize in migrating large-scale Informatica ETL workloads into Databricks. This is perfect for companies moving away from proprietary ETL toward a future-proof, cloud-native data engineering platform.
Assessment
Scan all Informatica mappings, workflows, and metadata
Provide a migration roadmap with time and effort estimates
Identify dependencies, reusable components, and transformation
Conversion
Convert Informatica transformations into Spark-native Databricks pipelines
Translate mappings and logic into PySpark notebooks
Maintain functional equivalence across all converted processes
Validation
Run automated tests to confirm accuracy and performance
Verify end-to-end workflows and data flow consistency
Document validation reports for traceability
Transition
Execute cutover with minimal business downtime
Set up real-time monitoring and alerting for early issue detection
Provide rollback and contingency support during production move
Enablement
Build a modern data engineering setup with Databricks and Delta Lake
Integrate MLflow for machine learning lifecycle management
Train teams on new workflows, pipelines, and monitoring tools
Why Choose Kanerika for Databricks Solutions
As a certified Databicks partner, Kanerika enables enterprises to adopt, deploy, and scale Databricks with confidence.
Proven Databricks Expertise
Deep experience in Databricks architecture, governance, optimization, and performance tuning.
End-to-End Implementation
Full lifecycle coverage including consulting, setup, training, and ongoing platform support.
Seamless Migration Experience
Successful migration of legacy systems and ETL platforms into modern Databricks environments
Strong Data Governance & Security
Secure operations aligned with ISO 27701, ISO 27001, SOC II, and compliance frameworks.
Optimized Performance & Cost Efficiency
Continuous tuning and resource optimization to reduce costs and maximize performance.
Long-Term Business Impact
Focused on faster insights, lower ownership costs, and smarter data-driven decisions
MIGRATION SOLUTIONS
How Enterprises Win with Kanerika and Databricks
71% Higher Reporting Accuracy with Informatica to Databricks
Impact:
- 71% Higher Reporting Accuracy
- 38% Reduction in Data Handling Costs
- 64% Faster Decision-Making
80% Faster Document Processing with Databricks Workflows
Impact:
- 80% Faster Document Processing
- 95% Improved Metadata Accuracy
- 45% Accelerated Time-to-Insight
50% Faster Data Workflows with Microsoft Fabric
Impact:
- Enhanced Data Efficiency
- Improved Decision-Making
- Scalable Data Infrastructure
Getting Started
Step 1
Free Consultation
Talk to our experts about your data challenges. We’ll assess your current setup and identify opportunities.
Step 2
Proof of Concept
We build a small pilot to demonstrate value. See results before committing to full implementation.
Step 3
Full Implementation
Once you’re confident, we execute the complete solution with minimal disruption to your operations.
Let’s Transform Your Business
Frequently Asked Questions (FAQs)
01What is Databricks and how does it work for enterprise data management?
A unified data and AI platform built on Apache Spark. It processes large datasets, supports real-time analytics, and enables machine learning workflows in one environment. Enterprises use it to eliminate data silos and accelerate insights.
02How long does Databricks implementation take for enterprise organizations?
Standard enterprise deployments take 4–8 weeks. This includes workspace setup, cluster configuration, governance implementation, and integration with existing data sources. Kanerika’s accelerators reduce timelines while maintaining compliance.
03Which cloud platforms support Databricks deployment?
Databricks runs on Azure, AWS, and Google Cloud Platform. We help you choose the right cloud based on your existing infrastructure, security requirements, and cost objectives.
04What is the difference between Databricks and traditional data warehouses?
Databricks combines data lake flexibility with warehouse performance. It handles structured and unstructured data, supports streaming, and integrates ML natively. Traditional warehouses are limited to structured data and batch processing.
05Can Databricks integrate with existing business intelligence tools?
Yes. Databricks connects with Power BI, Tableau, Looker, and other BI platforms. We configure secure connections and optimize queries for fast dashboard performance.
06What size datasets can Databricks handle efficiently?
Databricks scales from gigabytes to petabytes. Its distributed Spark architecture handles massive datasets with auto-scaling clusters that adjust compute resources based on workload demands.
07How does Databricks lakehouse architecture differ from data lakes?
A lakehouse combines data lake storage with warehouse reliability. Delta Lake adds ACID transactions, schema enforcement, and versioning. This eliminates data quality issues common in traditional lakes.
08What programming languages does Databricks support?
Databricks supports Python, SQL, Scala, R, and Java. Teams can use their preferred language within notebooks for data engineering, analytics, and machine learning workflows.
09Does Databricks require specialized infrastructure or hardware?
No. Databricks is fully cloud-based and serverless. You only need a cloud account (Azure, AWS, or GCP). Infrastructure provisioning, scaling, and maintenance are automated.
10What is the typical ROI timeline for Databricks implementation?
Most enterprises see measurable ROI within 3–6 months. Benefits include faster query performance, reduced infrastructure costs, shorter ETL runtimes, and improved data accuracy.
11How do you migrate Informatica workflows to Databricks?
We scan Informatica mappings and metadata, convert transformations to PySpark, validate logic and data, then execute cutover. Our automated framework handles 95% of conversion work while preserving business rules.
12What legacy ETL tools can be migrated to Databricks?
We migrate from Informatica, SSIS, Azure Data Factory, Talend, DataStage, and custom ETL scripts. Each migration includes automated conversion, validation, and performance optimization.
13How much downtime is required for ETL migration to Databricks?
Minimal. We execute parallel runs during transition, validate outputs, then switch over during low-traffic windows. Most cutovers complete in hours with zero data loss.
14What is the success rate of Informatica to Databricks migrations?
Our migration success rate exceeds 98%. Automated validation compares source and target data at every step. Rollback plans ensure business continuity if issues arise.
15Can you migrate on-premises data warehouses to Databricks?
Yes. We migrate from Teradata, Oracle, SQL Server, and other on-premises warehouses. Migration includes data transfer, schema conversion, query optimization, and performance tuning.
