{"id":28314,"date":"2022-11-25T12:44:33","date_gmt":"2022-11-25T07:14:33","guid":{"rendered":"https:\/\/blazeclan.com\/studies\/data-hub-solution-helped-the-customer-ebb-platforming-efforts-for-new-sources-by-50\/"},"modified":"2023-03-02T11:13:54","modified_gmt":"2023-03-02T05:43:54","slug":"data-hub-solution-helped-the-customer-ebb-platforming-efforts-for-new-sources-by-50","status":"publish","type":"case_study","link":"https:\/\/blazeclan.com\/asean\/studies\/data-hub-solution-helped-the-customer-ebb-platforming-efforts-for-new-sources-by-50\/","title":{"rendered":"Data Hub Solution Helped the Customer Ebb Platforming Efforts for New Sources by 50%"},"content":{"rendered":"<p>The customer is a global leading energy and solutions provider, exploring both renewable and hydrocarbon energy, ensuring excellence through their integrated business model. The energy giant was looking for a way to optimize its enterprise-wide access to data and bridge data gaps with a data lake and warehouse solution.<\/p>\n<h3>The Challenge<\/h3>\n<p>The customer wanted to establish an enterprise data hub (EDH) to meet and govern their data needs. They aimed at becoming a data-driven organization with this pilot project, which was a part of their initiative to create a Minimal Viable Product (MVP) on a pivot. The customer wants to aggregate and store data sets from multiple sources and consolidate them into a single infrastructure. Key challenges involved<\/p>\n<ul>\n<li>Restrictions in the deployment environment.<\/li>\n<li>Providing data in the desired format at the desired frequency.<\/li>\n<li>Requirements to change internal data collection\/entry process.<\/li>\n<li>Lack of pooled resources.<\/li>\n<\/ul>\n<h3>The Solution<\/h3>\n<p>Blazeclan advised the customer to leverage the AWS cloud services to achieve a secure, scalable and high-performing data architecture. This will offer them with efficient consolidation and governance of data, enterprise-wide visibility &amp; access, and automated reporting.&nbsp;<\/p>\n<p>The solution will enhance the frequency of updates, thereby allowing the customer to focus on data analysis and implement preventative measures. The whole MVP solution involved use of a hybrid cloud environment. The data from SAP was processed and onboarded using Azure and the rest of the data sources were onboarded using AWS cloud.<\/p>\n<h3><strong>The Solution Approach Followed<\/strong><\/h3>\n<ul>\n<li>Leveraging the approach of ETL using Talend to process data through AWS architecture and serve data to Pivot.<\/li>\n<li>Develop ETL using data sources of the incident management system (IMS), electronic Permit to Work (ePTW), and plant information (PI), which will be consumed by the Pivot.<\/li>\n<li>The data has been collected and processed in the AWS infrastructure using various tools and services.<\/li>\n<li>Visualization logics and KPIs have been used to improve operational excellence by leveraging the PI.<\/li>\n<\/ul>\n<p>The implemented solution triggers a series of automated processing pipelines to process data according to the model and push it into the data warehouse. The data is consumed in a form of report which highlights analytics and statistics for making informed decisions.<\/p>\n<h3>Benefits Achieved by the Customer<\/h3>\n<p><strong>High Scalability:<\/strong> The data lake solution provided the customer with the ability to scale their infrastructure according to the changing business demands. The solution further enabled a new auto-scaling feature with minimum or zero downtime.<\/p>\n<p><strong>Automation:<\/strong> Automated data collection, storage and management enabled the customer\u2019s application teams to scale their deployment speed. Automation and data ingestion enables the customer to have a consistently updated view of business performance and customer behaviour.<\/p>\n<p><strong>Analytics-Driven Business decisions:<\/strong> Consolidation of all data sources in a single platform facilitated the customer in data accessibility and analysis. They were able to glean incisive insights from the analysis of data that enabled informed decision making.<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/blazeclan.com\/wp-content\/uploads\/2020\/10\/Value-Additions-_-Petronas-Data-Lake-_-Case-Study-1.png\" alt=\"\" width=\"100%\" class=\"alignleft size-full wp-image-22154\"><\/p>\n<h3>Tech Stack<\/h3>\n<table class=\"table table-hover\">\n<tbody>\n<tr>\n<td>Talend<\/td>\n<td>Amazon EC2<\/td>\n<td>Amazon S3<\/td>\n<\/tr>\n<tr>\n<td>Amazon Redshift<\/td>\n<td>Amazon API Gateway<\/td>\n<td>AWS IAM<\/td>\n<\/tr>\n<tr>\n<td>AWS KMS<\/td>\n<td>Amazon RDS<\/td>\n<td>Amazon VPC<\/td>\n<\/tr>\n<tr>\n<td>AWS Certificate Manager<\/td>\n<td>AWS Firewall Manager<\/td>\n<td>Amazon Cloudwatch<\/td>\n<\/tr>\n<tr>\n<td>AWS Aurora Serverless<\/td>\n<td>AWS Lambda<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"<p>The customer is a global leading energy and solutions provider, exploring both renewable and hydrocarbon energy, ensuring excellence through their integrated business model. The energy giant was looking for a way to optimize its enterprise-wide access to data and bridge data gaps with a data lake and warehouse solution. The Challenge The customer wanted to [&hellip;]<\/p>\n","protected":false},"featured_media":12517,"parent":0,"menu_order":0,"template":"","case_category":[3877,3922],"case_tags":[4227,4152,4107,4162,4147],"class_list":["post-28314","case_study","type-case_study","status-publish","has-post-thumbnail","hentry","case_category-big-data-analytics-asean","case_category-datalake-asean","case_tags-automation-asean","case_tags-big-data-asean","case_tags-cloud-asean","case_tags-data-analytics-asean","case_tags-data-lake-asean"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data Hub Solution Helps Ebb Platforming Efforts for New Sources by 50%<\/title>\n<meta name=\"description\" content=\"Data Hub Solution Helped the Customer Ebb Platforming Efforts for New Sources by 50%\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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