Unlock the Value of Data from the Talent Management Enterprise

The Leading Provider of Engaging Mobile Talent Management Solutions
AMPOS is a leading SaaS solution provider of engaging mobile talent management solutions in Asia. To help their customers deal with the fast-changing dynamic working environment, AMPOS provides an integrated mobile talent management solution that enables organizations to have efficient two-way communications, provide structured online and in-person purpose-driven learning journeys, and real time recognition of positive behaviors.

“Help People Do Better”
Talent development is the foundation for business sustainability. AMPOS’s mission is to “Help People Do Better”. Organizations can provide a comprehensive employee experience through AMPOS application from onboarding, on-the-job learning, real-time behavior recognition, goal monitoring, to corporate culture sharing.

During COVID-19, for example, AMPOS provided a free module to help the companies effectively guide their teammates on emerging through tricky situations during this challenging period, such as monitoring employees’ health status, delivering the latest daily news and epidemic prevention knowledge and providing the online courses. In addition, AMPOS offers a gamified mechanism to encourage employees to have better learning paths leveraging training courses and achieve higher performance.

Through AMPOS’ platform, customers can gather insight on team behaviors, communication efficiencies, training progress and results, and company culture. When dive deep into many of the data collected through AMPOS platform, customers can often find answers to many of their business problems. However, AMPOS struggles to keep up with the demand from customers in a scalable manner.

Data Democratization is the Top Priority
AMPOS has hundreds of TB data which are scattered in multiple databases, making it very time-consuming and labor-intensive to collect, organize, and visualize enterprise reports – a typical data problem called data silos. Furthermore, the increasing demand for reports becomes overwhelming. The tedious and complicated data processing procedure stops data engineers from focusing on analyzing data and getting valuable insights, and impacts customer service quality.

“Although we are fairly advanced user of AWS services, we are new to AWS data lake offering. Instead of having our engineers to learn through trial-and-error, we are better off hiring experts from eCloudValley to help us build a data lake solution while have our team focus on developing our product. ”— AMPOS PM, Lily Feng

As a born-in-the-cloud company, AMPOS knows that it is necessary to immediately solve the problems caused by data silos. However, with the rapid expansion of business, AMPOS does not have enough dedicated time and bandwidth to support the data aggregation problems and data platform problems.

AMPOS’s talent management system has been running on AWS for a while, and AWS recommended eCloudvalley, one of the Premier AWS Consulting Partner, to be their partner. “eCloudvalley Data and Analytics Team with abundant hands-on experience on AWS cross GCR and ASEAN handles specifically data solution consultants and engineering, including building data platform leveraging data lake. Through their professional consultation, we believe that the solution provided by eCloudvalley can help us arrange resources accurately and achieve data democratization in a short time”, said Chieh Lee, AMPOS DevOps manager.

Data Silos to Data Lake
eCloudvalley provides a centralized data platform solution building a data lake on AWS. It fixes the problems of the low performance of data processing and analytics caused by the growing volume of AMPOS data and helps AMPOS have agile operations. Also, all users can access the complete data and start complex data analysis and visualization according to different business needs.
There are three phases of the project to build the data platform solving the problem of data silos. The first stage is the data ingestion, which is the basis of establishing the ETL foundation for their three major source databases. The second stage is the data transformation. They converted the original data from ETL to data that matches the business logic. The third stage is data consumption, which is the output API implementation and Amazon QuickSight implementation. Through three phrases, AMPOS can capture the required data through a friendly interface, reduce the cost of back-and-forth communication between end-users and engineers, and make the analysis process efficient and accessible.

Data Lake Accelerates Product Innovation
“The greatest benefit is that my team completely focuses on application development and spends more time coming up with new features” – AMPOS DevOps manager, Chieh Lee.

The previous architecture cannot carry the load of an increasing number of customers and diverse human resource development requirements in the market. After adopting the data lake, its advantage of high scalability makes generate high-quality real-time analysis reports quickly. Chieh mentioned that data lake provides a centralized repository that allows them to store all structured and unstructured data at any scale without limitation of data types and to solve the problem of data consistency. A centralized data platform breaks down data silos and helps reduce the time of report generation from 3 weeks to 3 days.

Data Lake accelerates the innovation of AMPOS’s products and provides customers with more value. AMPOS can effectively analyze the data collected internally, and they can also perform some advanced analysis by combining external data. They analyze past historical data to understand trends, optimize products based on the report, and formulate new products or strategies to enhance the customer experiences.
Solving customers’ business problem through motivating and growing their employees is AMPOS’ mission. The data solution provided by eCloudvalley enables AMPOS to provide that kind of value to its customers in a more scalable and efficient way, and expand to new markets.

2020-07-22T18:28:36+00:00 2020/07/14 |Insights|