Data Engineering and Analytics

Unlock the power of your data with Plakxa's comprehensive data engineering and analytics services. We offer end-to-end solutions that help businesses harness the full potential of their data and gain valuable insights for informed decision-making.

Our Services:

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Data Integration and ETL: Seamlessly integrate and consolidate data from multiple sources, including databases, APIs, and third-party platforms. Our experts design efficient Extract, Transform, Load (ETL) processes to ensure accurate and timely data extraction, transformation, and loading.

Data Warehousing and Management: Leverage our expertise in designing and implementing scalable data warehouses tailored to your business needs. We optimize data storage, organization, and retrieval, enabling easy access and analysis of large volumes of structured and unstructured data.

Data Modeling and Transformation: Our skilled data engineers develop robust data models that align with your business requirements. We employ industry best practices to ensure data consistency, integrity, and flexibility for efficient data transformation and analysis.

Data Cleansing and Quality Assurance: Ensure data accuracy and reliability with our data cleansing and quality assurance services. We identify and rectify inconsistencies, redundancies, and errors in your data, ensuring high-quality and trustworthy information for analysis.

Big Data Processing and Analytics: Leverage the power of big data technologies and analytics tools to extract meaningful insights from massive datasets. Our team utilizes advanced technologies like Apache Hadoop, Spark, and distributed computing frameworks to process and analyze data at scale.

Data Visualization and Reporting: Transform complex data into visually appealing and intuitive dashboards and reports. Our data visualization experts use industry-leading tools and techniques to present key insights in a visually compelling manner, facilitating easy understanding and decision-making.

Data Governance and Security: Ensure data governance and security with our comprehensive data management practices. We implement robust security measures and compliance frameworks to protect sensitive data and ensure regulatory compliance.

Why Choose Plakxa for Data Engineering and Analytics?

  • Expertise and Experience: Our team of skilled data engineers and analysts possesses deep expertise and extensive experience in data engineering and analytics across various industries.
  • Customized Solutions: We understand that each business has unique data requirements. We tailor our solutions to your specific needs, ensuring optimal outcomes and maximum value from your data assets.
  • End-to-End Support: From data integration and modeling to analytics and visualization, we provide complete support throughout the data engineering and analytics lifecycle, ensuring a seamless and streamlined process.
  • Actionable Insights: Our focus is on delivering actionable insights that drive business growth and innovation. We help you derive meaningful insights from your data, enabling you to make informed decisions and stay ahead of the competition.
  • Data Security and Privacy: We prioritize the security and privacy of your data. Our stringent security measures and compliance frameworks ensure the confidentiality, integrity, and availability of your data.

CASE STUDIES

Large US based Global Engineering Firm providing technical, professional and construction services wanted to design a scalable, metadata driven data ingestion service

A leading oil and gas company, based out of Malaysia, required a feature to wrangle data within the enterprise data hub. As part of the IoT data lake, wrangling supported the extraction of required triggers from the data produced by the producers.

Large oil and gas company wanted to automate their engineering drawing conversion capability

A large oil and gas company wanted to develop a catalogue of signatories of historical engineering drawings.

A events company in Singapore was required to deploy their events livestream. For each event, cloud
infrastructure was required to be deployed to support size and security requirement of the event

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