Ais Romney 2006 Slides 15 Database Design Using The Rea
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The document discusses the steps for designing a database using the REA (Resources, Events, Agents) data model. It describes the three steps to develop an REA diagram: 1) identify relevant events, 2) identify resources and agents, and 3) determine relationships. It provides an example of modeling the revenue cycle, identifying sale and receive cash as the key events that represent the economic exchange, and take order as another relevant event.
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Surendra Parimi
CS688 – Introduction to CRISP-DM and the R platform IP 1
Colorado Technical University
07/10/2019
Table of Contents
Introduction to CRISP-DM and the R Platform Organizational Background3
Organizational Background:3
CRISP-DM(Cross-industry standard process for data mining):3
Data Maturity:4
Role of Data Analyst:6
How Do we Implement the R Platform:6
R Modeling With Regressions and Classifications (TBD)7
Model Performance Evaluation (TBD)8
Visualizations With R (TBD)9
Machine Learning (TBD)10
References11
Introduction to CRISP-DM and the R Platform Organizational BackgroundOrganizational Background:
The organization I currently work for and planning to implement the techniques of the data analytics course is T-Mobile USA, which offers wireless mobile phone services to 0ver 80 million customers in the United States. It’s a huge enterprise with large scale information technology systems that support the business that T-Mobile does. The company is seeing significant growth in terms of business and therefore the IT systems that are supporting the business. Myself as a DEVOPS engineer works on deploying the code to these mission critical systems, host them and operate to make sure the systems are working as expected. As the land scape of our IT systems grow, we want to be able to identify the issues in our systems in advance so that we can prevent them before causing any outage to the business. To achieve such a result, our IT systems logs needs to be analyzed in-depth to unleash the critical insights about the system performance and apply the feedback to improve our systems.
CRISP-DM(Cross-industry standard process for data mining):
The CRISP-DM helps us ensure our data analysis adheres certain standards and CRISP-DM is a proven strategy worldwide. Corporations like IBM have further enhanced and or customized the standard and came up with their own methodology knows as ‘Analytics
Solution
s Unified Method for Data Mining/Predictive Analytics(ASUS_DM)’
The CRISP-DM methodology involves 6 different steps
Business Understanding: Building the knowledge about business requirements and objectives from functional aspect and transforming this knowledge as a data mining objective with an implementation plan.
Data Understanding: Involves the process of data collection from diverse sources of data, review and understand the data to be able to identify the problems which compromise data quality and also give the initial understanding of what the data can deliver.
Data Preparation: The data preparation phase covers all activities to build the final dataset from the initial raw data collected.
Modeling: Modeling techniques are based on the objective of the problem being tried. So, based on the problem, model is decided and based on the model, data is collected.
Evaluation: The evaluation phase is taken up once.
Deblina Dey - Resume
Deblina Dey is a data analyst with 3 years of experience in analytics and business intelligence tools like Tableau, Spotfire Cloud, and Qlikview. She has worked on projects in the telecom and life sciences industries developing dashboards, reports, and visualizations to provide insights into areas like cost analysis, resource management, and hardware asset tracking. Her experience includes requirements gathering, data analysis, report development, and ensuring delivery of analytics solutions.
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Data analytics is widely applied in various fields and industries, including business, healthcare, finance, marketing, sports, and many more. It plays a crucial role in helping organizations make informed decisions, improve operational efficiency, understand customer behavior, identify opportunities, and mitigate risks.
For More Details: https://datamites.com/data-analytics-certification-course-training-delhi/
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Bi concepts
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