Building a Modern Data Platform

Building a Modern Data Platform

Most modern software solutions today either generate data, consume and analyze data, or both. EarthWeb reports that an astonishing 3.5 quintillion bytes of data are generated daily, with people spending $1 million online every minute. Consider the amount of data generated by all those sales. With this exponential data growth, harnessing the volume, velocity, and variety of data becomes essential, granting decision-makers the power to steer a business away from potential demise and guide it towards a path to success.

Challenges and Solutions

Today, we'll delve into some of the data challenges we encountered while expanding our platform capabilities and how building a modern data architecture helped us overcome these challenges, better preparing us for the future. We will discuss this topic in two threads: data orchestration and data pipeline optimization.

Data Orchestration

  1. Event-Driven Orchestration: The life cycle of business data involves several stages, from creation and extraction to transformation, storage, and visualization. To accommodate the heterogeneous nature of these data processes, we orchestrate data pipelines using event-driven tools like Apache Airflow. This methodology ensures efficiency and scalability, making sure all data correctly travels through pipelines before ending up on the dashboards, while reducing the wait time between each process.
  2. Data Monitoring: As we incorporate more data features into our products, the complexity of business logic continues to grow. Failures or anomalies can occur in these ever-expanding pipelines. Therefore, we implemented an orchestration tool that provides valuable visibility into the overall health of our data platform. This central hub allows us to monitor all data pipelines from start to finish, quickly notifying team members in case of problems and providing root cause analysis.
  3. Distributing Computing: Scalability has always been one of our main goals when developing our software platform. We anticipate a significant increase in data volume processed by our system in the coming years. Building robust pipelines that can expand horizontally in computing power is imperative to our platform. Ideally, the orchestration system can dynamically distribute parallel computational power to each task based on the need and overall system load ensuring maximum efficiency in terms of throughput and cost.

Data Pipeline Layer

  1. Data Ingestion: At DataMetrics, we help many businesses gain insights from operational data, typically ERP systems, e-commerce platforms, and online marketing providers. Instead of a one-size-fits-all solution, we build integration connectors for each source system and customize them to suit the clients' needs. This ingestion layer translates and standardizes source information into data ready for processing by the DataMetrics platform, striking a balance between customization and scalability.
  2. Data transformation: In the transformation layer of the pipeline, highly specific and complex logic navigates through several critical parts of business data to produce valuable insights and a reliable data source for downstream tasks. This layer combines industry expertise with machine learning algorithm implementations. It is designed to be robust and adaptable, with flexibility to include more modern analytics like Machine Learning. The modular and flexible nature of this layer supports our most complicated and demanding data processes.
  3. BI Analytics: Business intelligence ties all aspects together, creating a high-performance reporting layer that serves as the source for final dashboard visualizations. The flexibility of this layer allows for expanding and adjusting business logic as it evolves over time, providing great adaptability for the data product.

As a technology-oriented company, we continuously strive to increase efficiency by leveraging the data platforms available today for data orchestration and data pipelines. We are excited to share these capabilities with you through our software-as-a-service platform, helping you harness your data for better business decisions.


Ray Fan
Ray Fan

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