Operations Analysis
Data Quality Management
Assessing Data Quality and Accuracy
Visualizing Performance Metrics
Workflows
Building Predictive Models using Machine Learning
Drive Innovation through Predictive Analytics
Competitive Advantage
Data Scheduling 
It involves determining when and how data is collected, processed, and analyzed to optimize business
operations and decision-making
...This process often includes data extraction, transformation, loading (ETL), and
analysis ...
Customer Strategy It encompasses various aspects of business
operations, including marketing, sales, customer service, and product development
...Prescriptive Analytics: Recommending actions based on data
analysis ...
Assessment Utilizes risk matrices and impact
analysis to evaluate threats
...Data Governance, Data Quality, Data Architecture, Data
Operations DAMA-DMBOK The Data Management Body of Knowledge outlines best practices and standards in data management
...
Data Quality Management Data Quality Management (DQM) is a critical aspect of business
operations that focuses on maintaining the integrity, accuracy, and usability of data throughout its lifecycle
...implementing DQM practices, including: Data Silos: Data stored in isolated systems can hinder effective data integration and
analysis ...
Assessing Data Quality and Accuracy Operational Efficiency: High-quality data reduces errors in
operations and enhances productivity
...Key aspects of data profiling include: Descriptive statistics (mean, median, mode) Data distribution
analysis Identification of missing values 2
...
Visualizing Performance Metrics This practice helps organizations monitor their performance, identify trends, and make informed decisions based on data
analysis ...Revenue Growth Rate Operational Metrics Metrics that assess the efficiency of
operations ...
Workflows They play a crucial role in enhancing productivity, ensuring consistency, and improving the overall efficiency of
operations ...Enhance the speed and accuracy of data
analysis ...
Building Predictive Models using Machine Learning In the context of business, predictive models are essential for making informed decisions, optimizing
operations, and enhancing customer experiences
...K-Means Clustering, Hierarchical Clustering, Principal Component
Analysis Reinforcement Learning Involves training a model to make decisions by rewarding desired outcomes
...
Drive Innovation through Predictive Analytics Data Processing: Cleaning and transforming raw data into a usable format for
analysis ...Operational Efficiency Predictive analytics can streamline
operations by forecasting demand and optimizing resource allocation
...
Competitive Advantage De Beers' diamond mining
operations ...Prescriptive analytics is a subset of business analytics that focuses on providing recommendations for actions based on data
analysis ...
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