Real-time Data Streaming
Unlock real-time insights, streamline data processing, and make swift, informed decisions for a dynamic, agile workflow.
Contact UsBenefits of Real-Time Data Streaming
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Real-Time Insights
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Increased Productivity
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Cost Optimization
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Improved Scalability
Problem
Inefficient Real-Time Data Processing
Traditional batch processing can't keep up with the need for immediate data analytics. This results in delayed insights, high operational costs, and difficulties in scaling to handle increasing data volumes.
Solution
Problem
Poor Resource Utilization
Do you struggle to balance resource allocation in a data streaming service to handle varying data volumes? Over-provisioning leads to unnecessary costs, while under-provisioning risks performance issues.
Solution
Problem
Lack of Real-Time Personalization
Delivering real-time personalized experiences to users, such as in e-commerce or content recommendations, requires rapid processing of user behavior data. Traditional batch processing falls short in delivering the immediate personalization that users expect.
Solution
What is Real-Time Data Streaming?
Are data fragmentation, growing data volumes, or low data quality holding you back? The reason might lie in poor data pipeline design and inefficient ETL processing.
Our expert team helps you streamline data extraction, transformation, cleansing, and integration processes for improved decision-making. We dive deep into your existing infrastructure to gauge its efficiency and reliability. Then, we design and deploy a new system, eliminating bottlenecks constraining your workflows.
The result? Faster analysis for real-time decision-making, cost savings, and increased scalability. Your data infrastructure becomes meticulously organized, and your processes run smoothly like parts of a well-oiled machine.
Achieve immediate insights — transform your workflow with data streaming.
We are certified partners of
Roadmap
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1
Foundation and Infrastructure
We define and document your organization's goals, specific needs, use cases, and expectations from the service.
We select the appropriate technology stack for your data streaming platform.
We integrate your data sources into the data streaming service and configure data pipelines and connectors to ingest real-time data. -
2
Real-Time Data Processing
We implement transformations and enrichments to clean, format, and prepare incoming data for analysis.
We design and the stream processing logic, which involves defining the real-time processing operations to be applied to the incoming data.
We select storage solutions (e.g., data lakes, databases) to archive historical data for future analysis. -
3
Monitoring, Scaling, and Optimization
We monitor the health and performance of your data streaming service, setting up alerts for anomalies, errors, or bottlenecks in data processing.
We perform scalability and load testing by simulating various traffic scenarios to identify areas for optimization.
We review the system's performance, identify areas for improvement, and apply enhancements.
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“Data experts from Valiotti quickly grasped the essence of the project and since then the team has been the strongest support for our analytics department.”
Case Studies
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AI Sales
Advanced analytics boosted AI Sales with revenue tracking, AI vs. human performance insights, real-time alerts, and improved bot strategies for higher efficiency.
Read more -
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betPawa
A Flexible and Scalable DWH system Re-Built from Scratch with Improved Data Processing Time and Quality
Read more
FAQ
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We are a team of professionals available to contribute our vast experience and skills to your project. Taking leadership roles in data engineering and analytics, we have been working in the field for over 3 years. The geography of our customers is impressive. You are welcome to check out our latest case studies with specific details on our success and customer satisfaction.
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Data analytics is the process of analyzing data to uncover insights, trends, and patterns to improve decision-making and optimize business processes. Data analytics services involve various techniques and means, such as statistical analysis, data visualization services, and analytics data stack BI tools.
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Data engineering is the process of designing, building, and maintaining data infrastructure. It involves developing and implementing data pipelines, warehouses, and other data storage and processing systems. Integrating data from multiple sources, a data engineer cleans and transforms it, ensuring that it is accurate, consistent, and accessible.
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The term analytics data stack refers to the set of technologies and tools commonly used in data engineering and analytics. It can be configured and customized to meet the specific needs and requirements of a company.
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A data analytics company can help you better understand your customers, their behavior, and their needs, optimize your business operations, and make pivotal data-driven decisions.
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A data analytics company can help you better understand your customers, their behavior, and their needs, optimize your business operations, and make pivotal data-driven decisions.
When do you need advanced analytics services?
You need advanced analytics services when you want to:
- forecast future events or outcomes,
- implement predictive analytics to envision customer behavior,
- optimize business operations and processes,
- build a recommendation system,
- test new ideas and hypotheses.