Data Engineering

Harponian® assists organizations with the adoption of cloud-based data engineering. This includes designing, building, and maintaining systems for collecting, storing, and analyzing data at scale.

Cloud-based data engineering plays a crucial role in ensuring that data is accessible, reliable, and ready for analysis by data scientists and business analysts.

• Data Collection

  • Development of systems to gather data from various sources, such as databases, APIs, and IoT devices

• Data Storage

  • Design and management of data storage solutions, including data lakes and data warehouses, to store large volumes of structured and unstructured data

• Data Processing

• Creation of data pipelines to process and transform raw data into a usable format. This involves cleaning, aggregating, and enriching data

• Data Integration

  • Integration of data from different sources to create a unified view, ensuring consistency and accuracy

• Data Security and Governance

  • Ensuring data privacy, security, and compliance with regulations

Harponian’s® consultants are Microsoft certified, and work with cloud-based data engineering services from Microsoft. These include the following:

• Azure Data Factory

  • A cloud-based data integration service that allows you to create, schedule, and orchestrate data workflows

  • It supports data movement and transformation from various sources to destinations

• Azure Synapse Analytics

  • An integrated analytics service that combines big data and data warehousing

  • It enables you to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs

• Azure Stream Analytics

  • A real-time analytics service designed to process and analyze streaming data from various sources, such as IoT devices, social media, and applications

• Azure Event Hubs

  • A big data streaming platform and event ingestion service capable of receiving and processing millions of events per second

• Azure Data Lake Storage

  • A scalable and secure data lake for high-performance analytics workloads

  • It allows you to store data of any size, shape, and speed, and perform all types of processing and analytics across platforms and languages

• Azure Databricks

  • An Apache Spark-based analytics platform optimized for Azure

  • It provides a collaborative environment for data engineers, data scientists, and business analysts to work together on data and AI projects 

Harponian’s® consultants are Amazon Web Services (AWS) certified, and work with cloud-based data engineering services from Amazon Web Services (AWS). These include the following:

• Amazon S3

  • A scalable object storage service that allows you to store and retrieve any amount of data at any time

• AWS Glue

  • A fully managed ETL (Extract, Transform, Load) service that makes it easy to prepare and load data for analytics

• Amazon Redshift

  • A fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and existing business intelligence tools

• Amazon Kinesis

  • A platform for real-time data streaming and analytics, enabling you to collect, process, and analyze real-time data streams

• AWS Data Pipeline

  • A web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources

• Amazon RDS

  • A managed relational database service that supports several database engines, including MySQL, PostgreSQL, and SQL Server

• Amazon EMR

  • A cloud big data platform for processing vast amounts of data using open-source tools such as Apache Hadoop, Spark, and HBase

• AWS Lake Formation

  • A service that makes it easy to set up a secure data lake in days, allowing you to store and analyze all your data in one central repository 

Harponian’s® consultants are Google Cloud Platform (GCP) certified, and work with cloud-based data engineering services from Google Cloud Platform (GCP). These include the following:

• BigQuery

  • A fully managed, petabyte-scale analytics data warehouse that allows you to run SQL queries on large datasets quickly

• Cloud Storage

  • A scalable, durable, and highly available object storage service for storing and accessing any amount of data

• Cloud Dataflow

  • A unified programming model and managed service for developing and executing a wide range of data processing patterns, including ETL, batch, and stream processing

• Cloud Dataproc

  • A fast, easy-to-use, fully managed cloud service for running Apache Spark and Apache Hadoop clusters

• Cloud Data Fusion

  • A fully managed, cloud-native data integration service for quickly building and managing data pipelines

• Dataplex

  • An intelligent data fabric that provides a unified way to manage, monitor, and govern data across data lakes, data warehouses, and data marts