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Data Engineering & ETL
- Data Engineering & ETL
About the Client:
A leading media and publishing company based in Saudi Arabia. The company focuses on publishing, printing, and distributing a diverse range of publications, reaching both local and international audiences.
Media and Publishing
Serverless Data Lake, Data Integration, Visualization, KPIs, REST API
The client has over 50 digital ventures, each of which generates more than 100M in data events per day from 10-15 sources. Each of them also had social media handles on platforms like Facebook, Instagram, YouTube, LinkedIn, Twitter, Snapchat, and TikTok. The client made use of social media to post articles, videos, and other posts which generated a huge amount of data in terms of engagements, posts, etc. The data was siloed and they were not able to generate any insights from the data. They wanted a system strong enough to accommodate not just the current data generated in the organization but also any future subscribers, queries and data sources.
Tringapps helped the client team to design and build a serverless data lake house with Amazon S3 as the storage service. This data lake architecture provided the client with a centralized, secure, and highly durable cloud-based storage system. Tringapps was able to extract data from various sources and load them to the data lake in AWS.
The whole solution was implemented in 6 months. Our team also helped in quickly building a visualization layer on top of the data lake to derive insights. This helped them to quickly define KPIs and view them on the go. Tringapps also built a querying layer on top of the data lake house to be used as a rest API. By making use of AWS services, Tringapps was able to decrease convolutions and costs associated with the development, which also provided critical data insights.
Tringapps built a serverless data lake for the company and performed an gathered from click-streams, social media, internet-connected devices, a integration of actionable data insights.
Ability to harness data from multiple sources, as well as options for futu other business-critical functions
Ability to gain deeper insights into their data in ways that traditional data
Centralize, consolidate and catalog your data and eliminate silos, offering downstream users a single place to look for all sources of data
Quickly and seamlessly integrate diverse data sources and formats
Cloud-scale centralized and scalable architecture that enables enterprise data science
Multiple levels of security, identity and access management, encryption, and compliance to secure their data
Less than a tenth of the cost of traditional solutions as in Serverless you pay only for what is used
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