
BUSINESS IMPACT
Real results at scale
Around the clock data support and management
Near real-time data processing and reporting
A huge amount of data managed effectively
High level of error detection and alerting
Continuous development in line with the evolution of technologies
Over 7 years of data management
The Challenge
Our client dealing with a growing, high volume of varied, complex data required advanced support and maintenance to avoid loss of data, ensure high uptime and enable data accessibility.
The Solution
Leading consumer electronics brand
Our client are a US-based, leading consumer electronics brand selling various electronic products such as LCD TVs, soundbars and operating systems for their smart TVs. They have been building innovative technology products for over two decades and are now an IPO listed company with an annual turnover of more than $2.1 billion. With a large consumer audience, our client collects huge volumes of TV data from their audience across the US.
Ensuring data availability, consistency and accuracy
Data availability for our client was crucial. They were dealing with vast volumes of varied, complex TV and commercial data. They collected the data from all users that have opted in across the US, and this large amount of data is coming in continuously. It was vital that the data was available for our client’s data science teams, accurate and full without any data drops or gaps.
Optimising 4 petabytes of client data
Ardent’s exceptional engineers work around the clock to provide data engineering support to help effectively manage client data. Our data engineering team manage three Redshift clusters on behalf of the client, the first cluster contains the data for the previous month, the second cluster contains the data from the previous year and the third cluster is used for data sharing.
One of the biggest technical challenges that our data engineering teams succeeded on was processing the data and delivering it to the client in near-real-time. Our expert data engineers were able to provide near real-time availability of the data to our client’s data science team by processing data in 6 parallel streams in Redshift, considerably increasing the speed at which the data available to the client.
The data is processed, transformed, loaded, and sent to the client ensuring that its free of duplication and errors and is delivered in near-real-time.
Advanced error detection and alerting
As part of the solution, our data engineers have the highest error detection and alerting processes in place with PagerDuty to ensure that any issues that arise are dealt with quickly and efficiently. Our teams are consistently monitoring the data around the clock to make certain that any errors that arise are communicated with the relevant teams and resolved immediately. This is to make sure that there is no loss of data which can lead to data gaps.
Progression of technologies
We have been managing our client’s data for over seven years and how we do this has developed over time with the evolution of technologies. With a long-term project, consistent optimisation is key. Therefore, we are currently, we are in the process of moving data processing from Amazon S3 to AWS Firehouse for quicker data ingest and reporting for the client.
Actionable commercial insights
The Ardent data engineering team have been effectively managing our client’s data for over seven years and continue to innovate and evolve to improve data speed, accuracy and performance. We ensure that the client has peace of mind knowing that their data is in safe hands with Ardent and is managed effectively, securely and in line with industry best practices. Our client are able to use the data collected to gain meaningful insights for commercial benefit, boosting revenue and growth.
The Results
Ardent manages and continuously optimises approximately four petabytes of television and commercial data, with six parallel Redshift processing streams, 24/7 monitoring and more than seven years of ongoing service.
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INDUSTRY
Technology
SOLUTION
Python, Amazon SQS, Amazon S3, Amazon EC2, Amazon Redshift, Razor SQL Tool, PuTTY, Git, WinSCP, PagerDuty
KEY FACTS
4 PB
Data managed across the client environment
3
Amazon Redshift clusters
6
Parallel processing streams
7+ years
Ongoing data management
24/7
Monitoring and support
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