DataOps Services

Transform your data into a powerful asset that drives informed decisions and adapts to your evolving requirements with our DataOps services.

20+

DataOps projects

Transform your data into a powerful asset that drives informed decisions and adapts to your evolving requirements with our DataOps services.

20+

DataOps projects

Why businesses might need DataOps consulting services

Inefficient data engineering processes

Excessive manual work in data operations

Inconsistent data quality

Challenges in data security and compliance

Slow adaptability to changing business needs

Data engineering bottlenecks

Inefficient data engineering processes

Innowise’s team implements automated data pipelines with orchestration tools like Apache Airflow and Apache NiFi to enable consistent loading of data into target systems coming from different sources.

Excessive manual work in data operations

Through automation of repetitive tasks and the use of scripts and workflow management systems, we reduce manual effort, allowing teams to concentrate on more strategic activities.

Inconsistent data quality

We design frameworks that automate validation checks in the data quality process, which maintain accuracy, consistency, and completeness at all layers of the data pipeline.

Challenges in data security and compliance

Our experts protect sensitive data with encryption, enforce strict access controls, and conduct regular audits — all to prevent unauthorized access and provide adherence to regulations.

Slow adaptability to changing business needs

To address slow responses to changes in business needs, we design flexible data architectures using cloud-based solutions like AWS or Azure — enabling rapid scalability and easy modifications.

Data engineering bottlenecks

Our approach includes establishing solid monitoring systems to track performance, holding training, and implementing continuous improvement practices through regular assessments.

Inefficient data engineering processes

Excessive manual work in data operations

Through automation of repetitive tasks and the use of scripts and workflow management systems, we reduce manual effort, allowing teams to concentrate on more strategic activities.

Inconsistent data quality

We design frameworks that automate validation checks in the data quality process, which maintain accuracy, consistency, and completeness at all layers of the data pipeline.

Challenges in data security and compliance

Our experts protect sensitive data with encryption, enforce strict access controls, and conduct regular audits — all to prevent unauthorized access and provide adherence to regulations.

Slow adaptability to changing business needs

To address slow responses to changes in business needs, we design flexible data architectures using cloud-based solutions like AWS or Azure — enabling rapid scalability and easy modifications.

Data engineering bottlenecks

Our approach includes establishing solid monitoring systems to track performance, holding training, and implementing continuous improvement practices through regular assessments.

Get comprehensive DataOps services

Our DataOps services focus on building efficient, scalable, and secure data environments — allowing businesses to make real-time decisions

Data pipeline automation

We automate data workflows to minimize manual intervention and accelerate the delivery of valuable insights.

Data integration

Our DataOps engineers apply cleaning, transformation, and synchronization techniques to guarantee data consistency throughout multiple sources.

Data quality management

While providing DataOps services, our team strategically implements checks and validations to maintain data accuracy and reliability.

Data governance

We handle data governance by setting clear policies, managing metadata, providing access control, and maintaining data quality.

Data security and compliance

Innowise guarantees adherence to industry standards like GDPR, HIPAA, and others — managing data handling to prevent breaches and guarantee legal conformity.

DataOps strategy and consulting

Our consulting experts create aligned custom strategies to help improve data accuracy, simplify processes, and speed up time-to-insight.

Make the most of your data with Innowise! We’re ready to make your data more reliable and accessible for analysis.

Industries we serve

Finance & banking
Healthcare
Retail & eCommerce
Telecommunications
Manufacturing & supply chain
Energy & utilities
Automotive
Insurance
Transportation & logistics

Finance & banking

DataOps supports banks and financial institutions in maintaining compliance with regulatory requirements by providing automated, auditable data trails.

Improved financial reporting and decision-making processes
Boosted fraud detection
Simplified compliance with financial regulations

Healthcare

Managing sensitive patient data across various systems, complying with regulations, and using real-time analytics for improved patient care highlight the need for reliable DataOps strategies.

Real-time patient monitoring
Automated compliance and data security
A holistic, up-to-date view of each patient’s health

Retail & eCommerce

DataOps plays a key role in automating data integration across multiple channels, including online stores, POS systems, and customer touchpoints.

Personalized customer engagement
More targeted marketing strategies
Optimized inventory forecasting

Telecommunications

With automated collecting and processing of data from different network elements, telecom companies can detect and resolve performance issues early.

Real-time monitoring and optimization of network performance
More tailored and responsive service offerings
Faster deployment of new services and network updates

Manufacturing & supply chain

By automating data workflows, well-crafted DataOps allow manufacturing & supply chain businesses to analyze production and inventory data effectively.

Improved production schedules and minimized downtime
Higher supply chain visibility and responsiveness
Optimized distribution and reduced consumption waste

Energy & utilities

Automated data pipelines allow energy and utility organizations to optimize resource allocation and predictive maintenance.

Improved resource allocation and consumption tracking
Faster response to outages and maintenance needs
Accurate and timely reporting through automated compliance reporting

Automotive

In the automotive industry, DataOps automates the flow of vehicle data to enable real-time diagnostics, helping manufacturers quickly identify and address performance issues.

Real-time diagnostics and performance monitoring
Reduced breakdowns and increased reliability
Improved customer insights

Insurance

Our DataOps services can automate data workflows, allowing insurers to process claims more efficiently and assess risk with greater accuracy.

Up-to-date risk models for faster underwriting decisions
Faster claims data processing
Personalized customer services

Transportation & logistics

DataOps helps integrate data from shipping companies, warehouses, and fleet management systems, providing real-time visibility into the movement of goods.

Higher delivery accuracy and reduced transit times
Reduced delays and mismanagement
Higher supply chain transparency

Case studies

Our approach to DataOps services

In providing DataOps as a service, we adopt a collaborative approach — meaning we’re always open to discussions and ready to craft solutions for each demand that best fits the client’s current and strategic objectives.

Detailed project outline

We start with a clear project definition to make sure all stakeholders are aligned, preventing scope creep.

Precise cost estimation

Through strict risk assessments and realistic cost analyses, Innowise guarantees to maintain financial transparency from the start.

Collaborative approach

Our experts build an environment where effective partnership and mutual respect for each participant are the cornerstones.

Quality assurance

Quality control is paramount at every process stage — allowing us to identify and resolve issues early.

Solid data security

We employ encryption, controls for access, and continuous monitoring, enabling the safeguarding of sensitive information.

High scalability

Our approach guarantees that as your data needs evolve, our systems can expand and adjust accordingly.

Choose Innowise as a DataOps consulting company

Innowise brings in only the top 3% of software engineers so that you can work with people who excel in their field. We continuously improve on what we know, and with more than 17 years of experience, our proficiency grows through each project we undertake. Let’s grow and thrive together!

Pilip Tsikhanovich Head of Big Data Department at Innowise

“Our DataOps services are all-encompassing. We automate, monitor, and optimize the scaling of your data pipelines to guarantee that no matter how complex your infrastructure is, there will always be speed and consistency in the data output. With modern tools and best practices, see how our team clears bottlenecks for smooth data integration, management, and delivery.”

Our DataOps process

Planning

Business, product, and engineering teams come together to define metrics and standards for data quality and availability.

Building

Data engineers and data scientists create data products and machine learning models in this stage that will later power applications.

Integrating

This is the process stage when code and the data product are integrated into an organization's overall tech stack.

Testing

Testing may include data integrity tests, completeness tests, and checking data compliance with business rules.

Releasing and deploying

This stage implies planning the release, conducting thorough testing, and employing CI/CD practices to automate the process.

Operating and monitoring

Data pipelines run continuously, so we use statistical process controls to monitor for anomalies and address them early.

Planning

Business, product, and engineering teams come together to define metrics and standards for data quality and availability.

Building

Data engineers and data scientists create data products and machine learning models in this stage that will later power applications.

Integrating

This is the process stage when code and the data product are integrated into an organization's overall tech stack.

Testing

Testing may include data integrity tests, completeness tests, and checking data compliance with business rules.

Releasing and deploying

This stage implies planning the release, conducting thorough testing, and employing CI/CD practices to automate the process.

Operating and monitoring

Data pipelines run continuously, so we use statistical process controls to monitor for anomalies and address them early.

Planning

Business, product, and engineering teams come together to define metrics and standards for data quality and availability.

Building

Data engineers and data scientists create data products and machine learning models in this stage that will later power applications.

Integrating

This is the process stage when code and the data product are integrated into an organization's overall tech stack.

Testing

Testing may include data integrity tests, completeness tests, and checking data compliance with business rules.

Releasing and deploying

This stage implies planning the release, conducting thorough testing, and employing CI/CD practices to automate the process.

Operating and monitoring

Data pipelines run continuously, so we use statistical process controls to monitor for anomalies and address them early.

Want to transform your data processes? Our DataOps team can help you achieve improved data quality, faster data delivery, better collaboration between teams, and other measurable benefits.

17+

years of expertise

offices worldwide

1800+

certified experts

17+

years of expertise

offices worldwide

1800+

certified experts

offices worldwide

93%

recurring customers

17+

years of expertise

offices worldwide

93%

recurring customers

17+

years of expertise

17+

years of expertise

1800+

certified experts

93%

recurring customers

17+

years of expertise

1800+

certified experts

93%

recurring customers

Want to transform your data processes? Our DataOps team can help you achieve improved data quality, faster data delivery, better collaboration between teams, and other measurable benefits.

17+

years of expertise

offices worldwide

93%

recurring customers

1800+

certified experts

17+

years of expertise

offices worldwide

93%

recurring customers

1800+

certified experts

17+

years of expertise

offices worldwide

93%

recurring customers

1800+

certified experts

17+

years of expertise

offices worldwide

93%

recurring customers

1800+

certified experts

Core DataOps technologies we work with

Apache Airflow
Luigi
Prefect

Kubeflow Pipelines
Dagster

Apache Nifi
Talend
Fivetran

Stitch
Informatica PowerCenter
Apache Kafka

Great Expectations
Deequ
Talend Data Quality

Ataccama
Datafold

Collibra
Alation
Informatica Axon

Apache Atlas
Microsoft Purview

Apache Kafka
Debezium
Google Cloud Dataflow

Apache Flink
Confluent

AWS KMS
Apache Ranger
Snowflake Security Features
Databricks Data Governance

Okta
OneTrust
BigID
HashiCorp Vault

DataKitchen
Unravel
StreamSets

Cognizant
Wipro
Tata Consultancy Services
(TCS)

Recognized among the best,
by the best

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Choose your pricing model

Fixed-price

This option means the price is agreed upon and calculated based on the anticipated time and effort required. You pay a set amount for a defined scope of work, getting predictability. However, it provides limited flexibility for changes throughout the project.

Time & material

This option means you pay for our team’s actual hours worked. The cost varies based on the time spent and the specialists involved. This approach enables adjustments during the project, with additional hours charged as needed.

What our customers think

Egzon Gajtani Strategic Projects Coordinator Tangoo Professional Network

“We were highly satisfied with the outcome of the project and the deliverables that Innowise delivered. They were highly responsive and timely in their communication, which allowed for smooth and efficient collaboration.”

Industry IT services
Team size 2 specialists
Duration 6 months
Services Staff augmentation

Joakim Rosen Lead Developer YouWish AS

“Innowise has completed many projects and consistently performs well on their tasks. Their results-driven approach allows them to quickly scale their efforts depending on the required deliverables.”

Industry Consumer products
Team size 4 specialists
Duration 28+ months
Services Staff Augmentation, Retail Company, TypeScript, PHP, eCommerce

Gian Luca De Bonis CEO & CTO Enable Development OÜ

“We are impressed with their flexibility and willingness to find solutions for challenging situations. They actively assisted in every kind of situation. The team's willingness to deliver optimal results ensures the partnership's success.”

Industry IT consulting
Team size 8 specialists
Duration 36 months
Services Staff augmentation

FAQ

They differ in the areas they target: DataOps targets data processes, while DevOps targets software delivery. DataOps is all about automating data pipelines and continuous integration to increase efficiency and quality in data management and analytics. DevOps, on the other hand, amplifies the collaboration between software development and operation to deliver software reliably.

Both methodologies are designed to improve collaboration, efficiency, and quality, but they target different aspects of data and machine learning workflows. While DataOps focuses on the data lifecycle and analytics processes, MLOps covers the model deployment and operation aspects of machine learning.

Certainly! You just have to get in touch with us, and we will work with you to closely evaluate your existing systems and identify the ways and means to optimize them. We guarantee a frictionless integration effort to maximize your data workflows and improve collaboration across your teams. Let’s get started!

Feel free to book a call and get all the answers you need.

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