Data Engineering and Governance

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Organizations need to be agile with evolving customer demands and preferences. Even when they are saddled with complex tech, data, and cloud infrastructure, enterprises need an efficient, reliable, and trustworthy data life cycle. How do organizations achieve agility? The foundation is set by the data engineering and governance practices for businesses including:

A trustworthy data management practice and security controls enabling analytics and AI models

Realizing the value and actionable intelligence from the fast-growing enterprise data pool

Sustainable data preparation methodologies to access insights from structured and unstructured data

Our Data Engineering Services

Data Ingestion

Integration of data from multiple sources and handling of structured, semi-structured, and unstructured from stream and batch processing.

Data Storage ETL/ELT

Extraction, transformation, and storing of data in various relational, big data, and cloud storage depending on the format, volume, and velocity of data

Data Lake and Data Warehousing

Aggregate your data seamlessly to establish a single source of truth and enable faster processing for insights.

Data Pipelines

Building automated, reusable and independent data workflow pipelines to transfer data and process batch and real-time data.

Data Architecture

Design multi-cloud solutions, optimization of data lake and data warehousing platforms for integrating multiple functional systems.

Data Mesh and Data Fabric

Modern decentralized approaches and evolving technology implementations to leverage data as an asset with appropriate ownership and controls.

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Profiling, cleansing, matching, stewardship, and analysis to determine the right value of data. Knowledge-driven quality controls for data of any size or format.

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Audit and Regulatory impact assessment partnering with your data and compliance teams.

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MDM implementations planned across multi-domains through scalable and reliable architecture.

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Smarter data security solutions with visibility, automation, and protection against emerging threats.

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Data Quality

Profiling, cleansing, matching, stewardship, and analysis to determine the right value of data. Knowledge-driven quality controls for data of any size or format.

Regulatory Compliance

Audit and Regulatory impact assessment partnering with your data and compliance teams.

Master Data Management

MDM implementations planned across multi-domains through scalable and reliable architecture.

Data Security

Smarter data security solutions with visibility, automation, and protection against emerging threats.

How Do We Do It?

Our experts at Saxon leverage a consultative approach to identify your data challenges and leverage data engineering, governance, and modernization expertise to evolve you into a modern data ecosystem.

Gap analysis, current state, future state, and map solutions for the organization’s insights goals.

Modernize data architecture and information consumption, and establish methodologies for data discovery, virtualization, and delivering data models at scale.

Methodologies for data pipeline automation, reusability of data assets, and establishing pre-built cleansing routines and data preparation.

Monetize data assets to empower stakeholders to leverage governed self-service data management and analytics tools for rapid insights.

Industry Insights

Application Modernization in Manufacturing

Data Governance: Importance and best practices

Do you want your organization to be data-driven? Then we suggest that you consider having data governance in place. In this article, you will find out what exactly it is, why it is important, why it isn’t optional, and the best practices for it. 

Microsoft Fabric – A one-stop-shop data analytics platform

Microsoft unveiled a unified analytics platform called Microsoft Fabric at the Build 2023 event. How will Fabric make a difference for businesses? 

8 Interesting Data Engineering Trends in 2023

To extract quality insights data engineering practices are the first step. So, let us look at a few data engineering trends in 2023. 

Why do you need Governance for Microsoft Power Platform?

The low-code development has opened new avenues for organizations and the rise in citizen developers is prominent. 

Saxon’s End-to-end Solution​

Are you looking for a one-stop solution that can automate your data pipelines and perform a few auto-cleansing routines and create a dashboard in a day?

With in-built data engineering components, pre-built dashboards, and industry-specific AI and ML use cases, InsightBox operates with efficiency at the nucleus.

InsightBox addresses the needs across your data lifecycle by connecting your data sources, organizing and preparing data for insights, and simplifying dashboards and predictive insights.

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Best Data Engineering Practices – Need

Reliable data structures

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Data quality utmost need

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Real-time data processing

Monitoring of data pipelines

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Data Engineering and Governance Services

Don’t let data siloes and bad data impact your business decisions. We have helped enterprises across industries transform their data governance model with industry-leading tools and best practices. Let’s help you to unleash the true potential of your data.

Drop Us Your Query

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radhika

Meet Our Expert

Radhika is a solution architect and experienced product owner with a strong track record of converting business requirements into scalable technology solutions. With over 16 years of experience, she specializes in architecting and implementing enterprise data solutions for delivering actionable intelligence. Her expertise provides thought leadership and technical guidance to ensure successful solution delivery. During her career, Radhika has created several solution accelerators and frameworks that streamline the data migration process, translating to substantial cost savings and reduced time to market high-quality solutions. She has leveraged Azure to architect, develop, and deploy cloud-based applications for data visualizations, resulting in increased data processing efficiency and effectiveness. Radhika’s proficiency extends to SQL Server, where she has acquired extensive database construction experience. She excels in designing and coordinating prototypes or proof of concepts, ensuring the successful execution of projects. Overall, Radhika’s diverse skill set and her deep understanding of Azure solutions and SQL Server make her an invaluable asset for businesses seeking innovative and efficient solutions to their technological challenges.

Ready to transform your data journey?

Fill out the form, and one of our experts will get in touch with you shortly to discuss your requirements and guide you through the next steps. 

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