Data Engineering

Data and Analytics help to improve the quality of business decisions based on scientific insights.

Enabling Data-Driven Transformations

Companies are faced with an overwhelming amount of data that is constantly increasing. To fully utilize their data resources, they must create data pipelines to transform and transfer data into a usable format for data scientists and other users. The potential for organizations to gain business value and improve customer service through data analysis is significant.

Our data engineering services improve data accessibility and usefulness for all users by assisting with data requirements, metadata management, security, and custom data processing.

Logix Guru’s approach focuses on maximizing the value of a company’s data through a solid data foundation and data mining. We address challenges that prevent companies from becoming data-driven competitors. Our services include designing and developing data pipelines (ETL and ELT), data products with APIs, and data quality management.

Our Capabilities

Data Architecture

Logix Guru is a company that specializes in building data lake architectures designed to facilitate the migration of data from existing databases to new ones. We ensure data quality during migration and keep the data secure and easily accessible to authorized users. Data lakes are a modern approach to data management that allows organizations to store, process, and analyze large amounts of data in its raw format, making it more flexible and cost-effective.

Data Ingestion

Logix Guru’s data engineering solutions are designed to address modern enterprises’ critical data management, processing, organizational, and storage concerns. These solutions can help organizations to effectively store, process, and analyze large amounts of data in its raw format, making it more flexible and cost-effective. They are intended to support the needs of various industries, such as finance, healthcare, retail, manufacturing, and more. Our Data engineering solutions can help in creating a data lake architecture, data pipeline, data governance, and also provide analytics and insights.

Data Governance

We maintain the integrity of data through strict data engineering practices, including implementing detailed guidelines and governance policies for all projects, and regularly conducting checks to ensure compliance. Our data engineering practices also include implementing robust data validation and cleaning processes, as well as continuous monitoring of data pipelines to ensure timely detection and correction of any issues.

Data Warehousing

Data warehousing is complex. Data warehouse, integration, enterprise data management services, data modelling and architecture, data governance, performance, and managed services are essential to our Software’s data engineering services.

Data Virtualization

Data virtualization is critical, and we ensure this with maturing architectures that meet your changing needs. We provide all your data in a single logical layer that is curated, secure, and serves a variety of users, reducing data bottlenecks, inconsistencies, and reuse.

Data Migration

Our team handles every aspect of your data migration, including strategy, growth, documentation, and content. We do this though data engineering solutions that help businesses solve their data migration problems.

Success
Stories

Data Migration Services for effective Sales Data Analysis

To migrate the sales data from the on-premises MySQL database to Redshift on AWS, an ETL process was established.
Utilizing PySpark has improved the feasibility and simplicity of data movement by 80%.
By implementing EC2 Firewall settings to regulate access to the instances, security protocols were developed for Amazon EMR.

Data Engineering and Security for a Mobile Engagement Platform

Redesigned data architecture to handle complex ETL operations and computing.
A centralised big data ecosystem that has been established, dispersed processing, and integrated reporting data.
With better security, data processing times dropped from three days to three hours.

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Data Engineering

Enabling Data-Driven Transformations