Data-Driven Digital Transformation
With the assistance of SoftServe, working together with Google Cloud, our client has been able to overcome the roadblocks of being a data-driven organization to deliver more insights to the organization. What resulted was a reduction in the total cost of ownership of the analytics platform by 20% and improvements in marketing operations by 45%
Being able to navigate through rapid digital transformation has never been so challenging. As a result, companies that do not leverage data-driven insights face significant roadblocks and can struggle to remain competitive. Recently, our client—a manufacturer of household appliances with revenue over $7B—faced this challenge as they sought to accelerate digital transformation and strengthen their dominance in the high-end appliance space.
An abundance of legacy systems, as well as highly volatile data sources and environments, made it hard for company stakeholders to hear from customers. In addition, it created obstacles for financial analysis and marketing operations. These challenges made it difficult to obtain data-driven insights that would empower them to make the right business decisions, for the benefit of their customers.
Our client's goal was to distinguish themselves by enabling data-driven business decisions throughout the organization using a data platform and applied data products model. The main aim was to pivot and decouple from source systems and remove volatility to deliver logical standardized and conformed data to respective users inside the organization.
Our client knew they needed to migrate and enhance the organization through a cloudbased data and analytics platform. Google Cloud was chosen by the client due to the hyperscalers data capabilities. However, assistance was required from a services partner to ensure the new platform was built to best practices and integrated into the clients’ organizational processes, all while being efficient and effective. SoftServe was chosen to help build a reliable, Google Cloud based system that would automatically:
- Load and prepare vast amounts of data from multiple data sources.
- Produce reports and metrics on social media campaigns.
- Generate reports on financial results, sales, and more.
The resulting system is highly scalable, CI/CD-ready, and optimized to process massive amounts of data with minimal latency.
The transformation continues. Currently, SoftServe are helping to re-form data ingestion and modeling to support use cases by creating reusable data assets and services, including:
- Delivery of data ingestion and modeling for finance, media, and marketing
- Migration of existing data pipelines to achieve compliance with data engineering standards
- Upscaling reusable value-added services
- Automation and continuous improvement of the data environment platform
SoftServe's partnership provides the technical implementation expertise needed to build a reliable and scalable data platform by:
- Building data ingestion pipelines with containerized Python scripts orchestrated via Cloud Composer and executed on top of the Google Kubernetes Engine.
- Utilizing Cloud Dataflow for data-heavy ingestion and modeling processes.
- Utilizing BigQuery as the modern in-cloud data warehouse.
- Introducing the infrastructure-as-code approach by using Terragrunt and Atlantis.
- Enhancing data platform monitoring and alerting with DataDog integration.
- Introducing access control framework, allowing significant improvement in GCP resource management and access.
- Supporting by establishing solution architecture required by our client while still following the latest trends in cloud data warehousing.
SoftServe's experts exceeded our client's expectations by:
- Building or improving multiple data pipelines for marketing analytics platforms for Facebook, Breezometer, Prospect, Google Ads, Boldchat, Sprinklr, and others to support major marketing advertising campaigns and sales efforts.
- Building from scratch media data pipelines from multiple source systems, such as the Facebook Campaign Manager, to generate data insights into supporting media.
- Building from scratch or reimplementing finance data pipelines to support financial decision making, improve speed, visualization, and data retrieval for overall efficiency. It was foundational for future enhancements to gathering insights from financial data.
- Implementing CI/CD, internal monitoring, security best practices, data studio dashboards, GKE cluster management, infrastructure automation, and cost optimization.
LET’S TALK about how SoftServe can help you break data silos and make a data-driven enterprise your reality