In Azure Data Factory, continuous integration and delivery means moving Data Factory pipelines from one environment (development, test, production) to another. Azure Data Factory utilizes Azure Resource Manager Templates to store the configuration of the various ADF entities (pipelines, datasets, data flows, and so on). Below CI/CD lifecycle in an…

For gaining the maximum value of data products, they should be delivered in a timely manner. Moreover, consumers should have confidence in the validity of outcomes. …

What is Azure Virtual Machine? — Azure Virtual Machines provides the flexibility of virtualization by maintaining the physical hardware that runs on it. To meet the needs, the number of VMs that any application is using can scale up and out. For tasks such as configuring, patching, and installing, the software dependent on the requirements and…

Azure App service(in short): Azure PaaS service is the platform that handles infrastructure so developers can focus on the core web apps and services. It provides enterprise grade security and compliance. The apps including Web Apps, API Apps, Mobile Apps or Function Apps(optional) runs in an App Service plan. It…

Aim: With provided 5 csv sales files, ingress the data, transform and load into master tables(star\snowflake) and display KPIs with BI tool. Tools Used: MySQL database docker, Metabase docker, cloud Virtual Machine, pandas libraries of python. Analyzing provided dataset: Salesman code can repeat depending on whether its active or not…

Diagram to follow: Infrastructure requirements for this activity: 3 Ubuntu 18.04 Bionic Beaver LTS of small 2 units tag it as Kube Master Kube Node 1 Kube Node 2 a. Install docker on all the three servers in preparation for standing up a Kubernetes cluster. Add docker repository GPG key…

Simulate Web Server Logs Install git : sudo yum -y install git 2. Clone github repository path on server: git clone gen-logs-python3-master.zip

Big data in Banking — •Fraud detection: Using machine learning techniques like anomaly detection, recognize fraud real time to prevent and minimize losses. •Minimize risk and compliance issues: Using big data can enhance model quality and analysis of risk management. …

Types of Big Data Analytics Descriptive: Describes the current state that answers what and when type of questions. Typically uses reports, dashboards, visualizations like charts and graphs. Predictive: An analysis of historical data to predict what might happen. Yields a forecast of a probable outcome. Prescriptive — This type of…