Azure Databricks Implementation

Unlock insights from all your data and build AI solutions with your Apache Spark environment in minutes.

As businesses grow, they generate massive amounts of data every day. They feel overwhelmed by the needs for bigger storage, faster processing, quicker insights, lower costs, higher security, and increasing regulations. Enterprises need to scale and modernize their data architecture and infrastructure to stay competitive and respond to the business and customer demands. They need to embrace the digital transformation journey with a modern data platform that can remove the feeling of being lost in the technology puzzle.

Why Embrace Azure Databricks?

Azure Databricks provides a unified set of tools for building, deploying, sharing, and maintaining enterprise-grade data solutions at scale. Use it to process, store, clean, share, analyze, model, and monetize datasets with solutions from BI to machine learning. Develop and deploy data engineering workflows, machine learning models, and analytics dashboards that power innovations and insights across an organization.

Data Engineering 

Azure Databricks provides large-scale data processing for batch and streaming workloads. Combining the power of Apache Spark with Delta Lake and custom tools, Azure Databricks provides an unrivaled ETL experience.

Data Analytics

Enable analytics using your most complete and recent data. Unlock accurate insights with Azure Databricks through analytical dashboards and operational reports at any scale.

Data Science

Simplify and accelerate data science on large datasets. The fully managed Spark clusters of Azure Databricks run data science workloads. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring.

AI and Machine Learning

Azure Databricks uses pre-installed, optimized libraries to build and train machine learning models and build AI solutions. Leverage one-click access to preconfigured environments for augmented machine learning with state-of-the-art and popular frameworks.

Azure Databricks Implementation Mastery

Zelusit can help you plan and efficiently incorporate Azure Databricks into your organization’s strategy. As a Gold Microsoft Partner, you can tap into our vast expertise and rely on us to help you guide the way to creating a secure and cost-efficient single shared repository of your data in the cloud.

Strategy Alignment and Roadmap

Zelusit will help you assess your current data strategy, level of cloud maturity and data environment. Based on the findings, we not only design your Databricks solution as per your requirements, but also create a roadmap for future development and advanced usage across the entire organization.

Solution Implementation

Zelusit will create the Databricks solution and necessary data pipelines for you, establish CI/CD pipelines, and make sure all security mechanisms are in place.

Security

Assure that all security mechanisms are in place. Tap into Zelusit’s expertise and benefit from best practices that have been implemented in numerous successful deliveries.

Training and Support 

We make sure your team is fully capable of managing the implemented Databricks solution and is comfortable working with it. Optionally, you can benefit from Zelusit’s managed services where we run and maintain the solution for you.

Azure Databricks Implementation Methodology

Discover current state infrastructure, challenges, and future state goals. With prioritized business requirements and processes, a high-level implementation design is defined, with a sprint planning and training program. 

Establish a landing zone that accounts for scale, network, security, governance, identity, and other technology solutions and integrations. Implement basic elements of business functionality to prove capability. Validate technology choices. 

Gather detailed requirements to create a detailed solution design and plan the current sprint. Implement user stories and develop the solution accordingly. Perform unit, system, integration and user acceptance testing (UAT). Create training materials and assets. 

Create and execute release management and deployment plans. Validate skill and service readiness and deliver trainings. Provide warranty and on-going support services to fix defects and performance issues. Evaluate the solution and the needs of other application support services.  

8x Faster Reporting with a DWH Solution in Azure Cloud
Energy and Utilities Success Story

8x Faster Reporting with a DWH Solution in Azure Cloud

Our client was resolute in its need to modernize applications and centralize its data infrastructure to create a single source for all information. Therefore, the company engaged Zelusit to help build a modern data warehouse in the Azure cloud.

Zelusit built a data warehouse solution in the Azure cloud that now serves as a single source of truth and turns data into actionable insights.

100%

cleaned and governed data

8x

faster regulatory reporting

1

source of truth for all data

Frequently Asked Questions

Azure Databricks provides big data analytics and AI with optimized Apache Spark, supporting Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn.

Databricks has a strong commitment to the open-source community and manages updates of open-source integrations in the Databricks Runtime releases.

The Azure Databricks platform architecture is composed of two primary parts: the infrastructure used by Azure Databricks to deploy, configure, and manage the platform and services, and the customer-owned infrastructure managed in collaboration by Azure Databricks and your company.

Delta Lake is a reliable, secure, and high-performance storage layer that supports both streaming and batch operations in data lakes. It provides a unified storage solution for structured, semi-structured, and unstructured data, replacing data silos. As a result, Delta Lake serves as a cost-effective and scalable foundation for a lakehouse architecture.

The Databricks Lakehouse platform blends the strengths of data lakes and data warehouses, providing the dependability, robust governance, and speed of data warehouses, as well as the flexibility, openness, and machine learning capabilities of data lakes. This approach simplifies your modern data stack by eliminating the data silos that traditionally separate and complicate data engineering, analytics, business intelligence, data science and machine learning. 

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