Databricks Lakehouse Platform
Process, analyze and share data and conduct advanced analytics at scale with Vivanti
Discover how Vivanti, a certified Databricks services partner, can help you to plan, deploy, migrate to, build on and manage your data, analytics and AI workloads with Databricks.


Based on Apache Spark, Databricks’ processing engine is heavily optimized and ideal for processing huge data workloads fast: From performing basic transformations and calculations on billions of rows of data, to training Machine Learning models. Not only does Databricks shine when processing data at scale, it’s highly flexible too. Databricks works well alongside major database vendors, can run on multiple clouds (AWS, Azure or GCP), and performs strongly using your coding language of choice. SQL, Python, Scala, Java and R all work with Databricks.
How We Can Help
Databricks + Vivanti: Creating a single, open platform for data, analytics and AI workflows
![]() ![]() Databricks trainingOur certified Databricks experts can train and upskill your data team to help you realize the full potential of your analytics and AI projects and solutions. |
![]() ![]() Readiness AssessmentMoving to Databricks can be a great way to unify your data and your data related initiatives. But, what do you need to do to prepare? Our Databricks Readiness Assessment reviews your existing data frameworks, processes, databases, data science and analytics tools. It outlines the changes you’ll need to make to adopt Databricks successfully. |
![]() ![]() ![]() Implementation planningEngage Vivanti’s Databricks experts, as we design an implementation strategy and roll-out plan to suit your timeframes, budget and overall data goals. |
![]() ![]() ML Ops ReviewWhether you’re already using Databricks, or are considering taking the plunge, our targeted ML Ops Review outlines how to streamline and optimize your operational practices at each step of the ML journey – from data ingestion and batching, model training and tuning, to runtimes and benchmarking. |
![]() ![]() Data governance strategyWhether you’re already a Databricks customer, or are looking to take the plunge, you need consistent ways of working with your data. Our team can assess your current practices against your desired goals and produce a recommended framework to facilitate overall data quality, management and governance. Work with us to ensure the security and integrity of your data as well as the accuracy of your data-based insights. |
![]() ![]() ![]() Databricks health checkFeeling like you could get more from your Databricks experience? Engage Vivanti to conduct a head-to-toe review of your Databricks environment to reveal opportunities for optimization. |
![]() ![]() Targeted POCsKnowing where and how to get value from an expansive data platform can be tricky. Work with Vivanti to deliver short, sharp Proof-of-Concepts to pinpoint and prove how Databricks can best achieve your advanced analytics and AI goals. |
![]() ![]() End-to-end platform deploymentEngage Vivanti to implement all aspects of the Databricks Lakehouse Platform: From data lake and warehouse builds, data architecture and data pipeline design, to creating analytical applications and machine learning models. |
![]() ![]() ![]() Delta Lake buildDatabricks’ Delta Lake provides an open storage layer, enabling you to perform both streaming and batch operations on your data lake. Let Vivanti help you build your Delta Lake, enabling you to combine structured, semi-structured, and unstructured data in one place to support all your data use cases. |
![]() ![]() Data migrationLooking to consolidate your existing data assets on Databricks? Vivanti will create and execute a custom migration plan to suit your needs, including stand-up, configuration and go-live support. |
![]() Data architecture & pipeline designWithout careful management, a data lake can soon turn into a data swamp. Vivanti consultants can design and build data architectures, pipelines and processes to accurately feed your Lakehouse. Be empowered to reliably combine data from different sources and conduct trustworthy analytics – from traditional BI and regulatory reporting, to data science and AI. |
![]() ![]() Reporting & analyticsEngage Vivanti to build the intuitive reports and dashboards needed to effectively share data-driven insights throughout your organization – from traditional trends analysis, through to predictive analytics. |
![]() ![]() ![]() ML pipeline buildVivanti will work with your team to harness Databricks’ Machine Learning solutions to build a full ML pipeline. Package includes: Business problem identification; data collection and cleaning; model building and training; deployment of model in production; model tracking and pipeline automation. |
![]() ![]() Managed data platformPut your trust in the Vivanti team as we actively monitor and optimize your entire Databricks environment as a fully managed service. |
![]() ![]() Monitoring & maintenanceMaybe you want to build your Databricks platform and do the ongoing engineering in-house. But, you’d like a hand maintaining the health of your environment. Engage Vivanti to build, undertake and own day-to-day monitoring and the routine updates required to keep your environment performing optimally. |
![]() ![]() ![]() Your on-call expertsKeep our consultants on speed-dial to help answer your burning questions, add grunt to important projects and extra dev bandwidth at crunch time. |
How We Can Help
Databricks + Vivanti: Creating a single, open platform for data, analytics and AI workflows


Databricks training
Our certified Databricks experts can train and upskill your data team to help you realize the full potential of your analytics and AI projects and solutions.


Readiness Assessment
Moving to Databricks can be a great way to unify your data and your data related initiatives. But, what do you need to do to prepare? Our Databricks Readiness Assessment reviews your existing data frameworks, processes, databases, data science and analytics tools. It outlines the changes you’ll need to make to adopt Databricks successfully.



Implementation planning
Engage Vivanti’s Databricks experts, as we design an implementation strategy and roll-out plan to suit your timeframes, budget and overall data goals.


ML Ops Review
Whether you’re already using Databricks, or are considering taking the plunge, our targeted ML Ops Review outlines how to streamline and optimize your operational practices at each step of the ML journey – from data ingestion and batching, model training and tuning, to runtimes and benchmarking.


Data governance strategy
Whether you’re already a Databricks customer, or are looking to take the plunge, you need consistent ways of working with your data. Our team can assess your current practices against your desired goals and produce a recommended framework to facilitate overall data quality, management and governance. Work with us to ensure the security and integrity of your data as well as the accuracy of your data-based insights.



Databricks health check
Feeling like you could get more from your Databricks experience? Engage Vivanti to conduct a head-to-toe review of your Databricks environment to reveal opportunities for optimization.


Targeted POCs
Knowing where and how to get value from an expansive data platform can be tricky. Work with Vivanti to deliver short, sharp Proof-of-Concepts to pinpoint and prove how Databricks can best achieve your advanced analytics and AI goals.


End-to-end platform deployment
Engage Vivanti to implement all aspects of the Databricks Lakehouse Platform: From data lake and warehouse builds, data architecture and data pipeline design, to creating analytical applications and machine learning models.



Delta Lake build
Databricks’ Delta Lake provides an open storage layer, enabling you to perform both streaming and batch operations on your data lake. Let Vivanti help you build your Delta Lake, enabling you to combine structured, semi-structured, and unstructured data in one place to support all your data use cases.


Data migration
Looking to consolidate your existing data assets on Databricks? Vivanti will create and execute a custom migration plan to suit your needs, including stand-up, configuration and go-live support.

Data architecture & pipeline design
Without careful management, a data lake can soon turn into a data swamp. Vivanti consultants can design and build data architectures, pipelines and processes to accurately feed your Lakehouse. Be empowered to reliably combine data from different sources and conduct trustworthy analytics – from traditional BI and regulatory reporting, to data science and AI.


Reporting & analytics
Engage Vivanti to build the intuitive reports and dashboards needed to effectively share data-driven insights throughout your organization – from traditional trends analysis, through to predictive analytics.
ML pipeline build
Vivanti will work with your team to harness Databricks’ Machine Learning solutions to build a full ML pipeline. Package includes: Business problem identification; data collection and cleaning; model building and training; deployment of model in production; model tracking and pipeline automation.


Managed data platform
Put your trust in the Vivanti team as we actively monitor and optimize your entire Databricks environment as a fully managed service.


Monitoring & maintenance
Maybe you want to build your Databricks platform and do the ongoing engineering in-house. But, you’d like a hand maintaining the health of your environment. Engage Vivanti to build, undertake and own day-to-day monitoring and the routine updates required to keep your environment performing optimally.
Your on-call experts
Keep our consultants on speed-dial to help answer your burning questions, add grunt to important projects and extra dev bandwidth at crunch time.
Why we love Databricks
Flexible data processing and unification at scale
1. Large-scale data processing
Databricks’ core architecture – Apache Spark – can handle large-scale data processing extremely well
2. Code in your language
Databricks offers the flexibility to write code in your language of choice – from Python and SQL, to Scala and R
3. Open Source
Databricks’ commitment to Open Source technology means you can use established tools like TensorFlow and PyTorch
4. Multi-cloud design
Databricks’ multi-cloud design means it can run on top of – and be easily added to your existing subscriptions for – AWS, Azure or GCP