{"id":28515,"date":"2022-11-25T12:44:43","date_gmt":"2022-11-25T07:14:43","guid":{"rendered":"https:\/\/blazeclan.com\/studies\/viewership-dashboard-helped-telekom-malaysia-enable-near-real-time-insights-for-better-decision-making-2\/"},"modified":"2024-03-18T18:27:08","modified_gmt":"2024-03-18T12:57:08","slug":"viewership-dashboard-helped-telekom-malaysia-enable-near-real-time-insights-for-better-decision-making","status":"publish","type":"case_study","link":"https:\/\/blazeclan.com\/india\/studies\/viewership-dashboard-helped-telekom-malaysia-enable-near-real-time-insights-for-better-decision-making\/","title":{"rendered":"Viewership Dashboard helped Telekom Malaysia Enable Near Real-Time Insights for Better Decision-Making"},"content":{"rendered":"<p>Telekom Malaysia Berhad (TM) is nation\u2019s leading integrated telecommunications provider that is on a continuous journey of enhancing and elevating the nation\u2019s telecommunications technology and services toward delivering connectivity to all Malaysians. They approached Blazeclan for help in building a reporting solution that performs sentiment analysis on Twitter and community forum data in near real-time.<\/p>\n<h2>The Challenge<\/h2>\n<p>TM was looking into a comprehensive solution to enable near real-time &amp; better visibility of TV viewership in view of their ever-increasing data. By understanding the customers&#8217; viewing behavior, TM intended to make data-driven decisions to grow their business.<\/p>\n<h3>Key Analysis Areas Included<\/h3>\n<ul>\n<li aria-level=\"1\">Actual user engagement at a particular hour which can be drilled down to respective channels.&nbsp;<\/li>\n<li aria-level=\"1\">Visibility of new or repetitive users based on daily interval.<\/li>\n<li aria-level=\"1\">Time vs. day user engagement to understand user behavior &amp; identify peak viewing hour\/day.&nbsp;<\/li>\n<li aria-level=\"1\">User engagement duration with a particular channel (average time spent)<\/li>\n<\/ul>\n<h2><b>The Solution<\/b><\/h2>\n<p>TM partnered with Blazeclan in developing a Near Real-time Viewership Dashboard. Blazeclan came up with a solution leveraging AWS Glue &amp; AWS Lambda for processing the voluminous data. The approach involved the use of multi-node AWS Redshift cluster. This cluster brought scalability &amp; efficiency in query resolutions for TM. For visualization purposes, AWS QuickSight was used in combination with SPICE for a rapid, real-time, in-memory calculation &amp; analysis. This was engineered for rapid, advanced calculations &amp; providing near real-time data for the dashboard.<\/p>\n<p><img decoding=\"async\" class=\"aligncenter size-full wp-image-22832\" src=\"https:\/\/blazeclan.com\/wp-content\/uploads\/2021\/03\/Value-Additions-_-Case-Study-TM-Viewership-Analysis-1.png\" alt=\"\" width=\"85%\"><\/p>\n<h2>The Approach<\/h2>\n<ul>\n<li aria-level=\"1\">AWS infrastructure implementation.<\/li>\n<li aria-level=\"1\">Data ingestion and data preparation.<\/li>\n<li aria-level=\"1\">Dashboard development.<\/li>\n<li aria-level=\"1\">Data warehousing.<\/li>\n<li aria-level=\"1\">Iteration, evaluation, and streamlining.<\/li>\n<\/ul>\n<h2>Architecture Diagram<\/h2>\n<p><\/p>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"alignnone wp-image-38321 size-full\" src=\"https:\/\/blazeclan.com\/wp-content\/uploads\/2022\/11\/22.jpg\" alt=\"\" width=\"1920\" height=\"1080\" srcset=\"https:\/\/blazeclan.com\/wp-content\/uploads\/2022\/11\/22.jpg 1920w, https:\/\/blazeclan.com\/wp-content\/uploads\/2022\/11\/22-300x169.jpg 300w, https:\/\/blazeclan.com\/wp-content\/uploads\/2022\/11\/22-1024x576.jpg 1024w, https:\/\/blazeclan.com\/wp-content\/uploads\/2022\/11\/22-768x432.jpg 768w, https:\/\/blazeclan.com\/wp-content\/uploads\/2022\/11\/22-1536x864.jpg 1536w, https:\/\/blazeclan.com\/wp-content\/uploads\/2022\/11\/22-1568x882.jpg 1568w\" sizes=\"(max-width: 1920px) 100vw, 1920px\" \/><\/p>\n<h2><b>Benefits Achieved by TM<\/b><\/h2>\n<p><b>Actionable Insights:<\/b> The cloud-based data pipeline and BI dashboard enabled TM&nbsp; to get actionable insights on their user viewing patterns and trends for making better decisions and bringing overall improvement in end-user experience.<\/p>\n<p><b>Serverless Architecture:<\/b> TM was offered with a serverless architecture that enabled greater scalability, high flexibility, and faster time-to-release. They were able to achieve all this while maintaining cost-effectiveness.<\/p>\n<p><b>High Performance:<\/b> The solution offered TM with the ability to perform complex calculations at scale. This was done by using an in-memory engine, SPICE, for faster load times and automated, periodic data refresh.<\/p>\n\n\n\n\n<h2>Tech Stack<\/h2>\n<table class=\"table table-hover\">\n<tbody>\n<tr>\n<td><span>Amazon S3<\/span><\/td>\n<td><span>AWS Athena<\/span><\/td>\n<td><span>AWS Glue<\/span><\/td>\n<\/tr>\n<tr>\n<td><span>Amazon QuickSight<\/span><\/td>\n<td><span>AWS Lambda<\/span><\/td>\n<td><span>Amazon CloudWatch<\/span><\/td>\n<\/tr>\n<tr>\n<td><span>Secrets Manager<\/span><\/td>\n<td><span>Amazon Redshift<\/span><\/td>\n<td><\/td>\n<\/tr>\n<\/tbody>\n<\/table>","protected":false},"excerpt":{"rendered":"<p>Telekom Malaysia Berhad (TM) is nation\u2019s leading integrated telecommunications provider that is on a continuous journey of enhancing and elevating the nation\u2019s telecommunications technology and services toward delivering connectivity to all Malaysians. They approached Blazeclan for help in building a reporting solution that performs sentiment analysis on Twitter and community forum data in near real-time. [&hellip;]<\/p>\n","protected":false},"featured_media":13037,"parent":0,"menu_order":0,"template":"","case_category":[3970,3880],"case_tags":[4280,4120,4155,4110,4165],"class_list":["post-28515","case_study","type-case_study","status-publish","has-post-thumbnail","hentry","case_category-advanced-analytics-india","case_category-big-data-analytics-india","case_tags-advanced-analytics-india","case_tags-aws-cloud-india","case_tags-big-data-india","case_tags-cloud-india","case_tags-data-analytics-india"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Viewership Dashboard helped Telekom Malaysia with Real-Time Insights<\/title>\n<meta name=\"description\" content=\"TM was looking for a solution to enable near real-time &amp; better visibility of TV viewership in view of their ever-increasing data.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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