1
Q
What are some Organization Challenges (in regards to data)?
A
Understanding and using their data to positively effect change within the business.
2
Q
What Types of Data Collected By Businesses
A
Transactional data, telemetry data, and signals from social media.
3
Q
What are some Data Impacts To Business Operations?
A
Tracking inventory, identifying purchase habits,detecting user trends, recommending purchases, determining price optimizations, and stopping fraud.
4
Q
What are Common Data Segments For Sales Pattern Analysis?
A
Day-over-Day, Week-over-Week, and Month-over-Month comparisons.
5
Q
What is the Importance of Storytelling in Data Analysis
A
It helps business leaders understand the data and make informed decisions.
6
Q
What is required to effect change based on data
A
The ability to act on the data and facilitate trusted business decisions.
7
Q
What roles are Data Analysts Partners
A
Data engineers and data scientists.
8
Q
What is the Key Aspect Of Data In An Organization
A
Ensuring that the story told with data reaches the right people and is easily discoverable.
9
Q
What do Data Analysis Uncover?
A
Insights and hidden value in large amounts of data.
10
Q
What is the Significance Of Reports?
A
Tell a story help drive better business decisions.
11
Q
What is the consequence if a business lacks a story?
A
It becomes difficult to understand what the data is trying to convey.
12
Q
What is the Significance of Data Analysis?
A
helps to find insights and uncover hidden value through storytelling.
13
Q
What is the Relationship Between Data Analysis And Business Decisions?
A
Accurate data storytelling drives better business decisions.
14
Q
What Does Reallocating Resources Mean?
A
Adjusting business resources to accommodate needs identified through data analysis.
15
Q
What are Metrics?
A
Helps in understanding the performance and impact of business activities.
16
Q
What is the Ultimate Goal Of Using Data In Businesses?
A
To positively impact the business and its bottom line.
17
Q
What is the importance Of Knowing When To Change Course
A
It allows businesses to adapt strategies based on data insights.
18
Q
What is the Key Benefit Of Making Precise Business Decisions Quickly?
A
It enhances competitiveness and provides a better advantage in the market.
19
Q
What is the role of a Data Analyst?
A
Using and applying analytical skills to influence the organization.
20
Q
Data analysts Role
A
Using and applying analytical skills to influence the organization.
21
Q
What is a Story?
A
Interpreting data to convey meaningful insights and narratives.
22
Q
What is the significance of a Story?
A
To ensure continuous engagement and understanding of data insights among stakeholders.
23
Q
What is Data Analysis?
A
process of identifying, cleaning, transforming, and modeling data to discover meaningful and useful information
24
Q
What are Data-driven Businesses?
A
Businesses that make decisions based on what the story says
25
What are the Categories of Data Analytics?
Descriptive, Diagnostic, Predictive, Prescriptive, Artificial Intelligence (AI)
26
Define Descriptive Analytics
Used to answer questions about what has happened based on historical data and summarizes large semantic models to describe outcomes to stakeholders
27
Define Diagnostic Analytics
Used to answer questions about why events happened by using findings from descriptive analytics to figure out the cause
28
What are Performance Indicators?
Investigated during diagnostic analytic to figure out why events got better or worse
29
What is the Diagnostic Analytics Process?
Identify Anomalies in the data (could be a change in a metric or a particular market), collect data that related to the anomalies, use statistical techniques to discover relationships and trends that explain these anomalies
30
Define Predictive Analytics
Used to answer questions about what will happen in the future by using historical data to identify trends and determine if they are likely to recover.
31
What are some Predictive Analytics Techniques?
A variety of statistical and machine learning techniques such as neural networks, decision trees, , and regression
32
Define Prescriptive Analytics
Used to answer questions about which actions should be taken to achieve a goal or target so that businesses can make more data-driven and informed business decisions.
33
Define Artificial Intelligence
simulation of human intelligence in machines that are programmed to think, learn, and adapt
34
Define Artificial Intelligence Analytics
Answers questions about your data and enables systems to process vast amounts of data, recognize patterns, and deliver insights with minimal human intervention.
35
Data Analysis Example
A retail business might look at historical data to see what items are popular and how much they should have in stock
36
What are the Different Roles On Data Team?
Business Analyst, Data Analyst, Data Engineer, Analytics Engineer, Data Scientist
37
Business Analyst
Analyzes data in terms of the business and is very similar to a data analyst (could be the same person)
38
Data Analyst
enables businesses to maximize the value of their data assets through visualization and reporting tools such as Microsoft Power BI
39
Data Analyst Responsibilities
Profiling, cleaning, transforming data; designing and building scalable and effective semantic models; work with the stakeholders to identify appropriate and necessary data and reporting requirements; turning raw data into relevant and meaningful insights; management of Power BI
40
Data Engineer
provision and set up data platform technologies that are on-premises and in the cloud
41
Data Engineer Platforms
relational databases, non-relational databases, data streams, and file stores
42
Data Engineer Responsibilities
use of on-premises and cloud data services and tools to extract, , transform, and load data from multiple sources and collaborate with business stakeholders to identify and meet data requirements.
43
What is the relationship between a Data Analyst and Data Engineer?
Work together so the data analysts can access the variety of data sources
44
Analytics Engineers
Bridge the gap between data engineering and analysis by curating data assets in data lakes or lake houses.
45
Data Scientist
Perform advanced analytics to extract value from data
46
Expiatory Data Analysis
Process by which descriptive analytics evaluate data
47
Five Key Areas of Data Analysis Prepare
Prepare, Analyze, Model, Manage, Visualize
48
Data Preparation
The process of profiling, cleaning, and transforming data so any inaccurate or missing data is fixed and the data is ready to be visualized.
49
What are Privacy and Security?
Assurances so that data is automatized or prevent people from seeing personal information when not needed
50
What is a Model?
Defining and creating relationships between tables so you can see how tables are related to each other
51
What are some Model Enhancements?
you can enhance the model by defining metrics and adding custom controls
52
What is the Impact Of A Model?
Allows organizations to gain insights into the data and makes reports more accurate, allows the data to be explored faster and efficiently, decreases time for the report writing process, and simplifies future report maintenance
53
Visualization
Solve business problems by using a well designed report to tell a story about the data.
54
Importance of Reports
help businesses and decision makers understand what that data means so that accurate and vital decisions can be made and drive the overall actions
55
Analyze
find insights, identify patterns and trends, predict outcomes by understanding and interpreting the information that is displayed on the report.
56
Advanced Analytics
enables businesses and organizations to ultimately drive better decisions throughout the business and create actionable insights and meaningful results
57
Manage
Managing the Power BI assets such as reports and dashboards.
58
Apps
valuable distribution method for your content and allow easier management for large audiences
59
Microsoft Power BI
A complete reporting solution that offers data preparation, data visualization, distribution, and management through development tools and an online platform
60
Primary Components of Power BI
Power BI Desktop (desktop application), Power BI service (online platform), Power BI Mobile (cross-platform mobile app)
61
Power BI Desktop
development tool available to data analysts and other report creators
62
Power BI Service
allows you to organize, manage, and distribute your reports and other Power BI items
63
Power BI Mobile
allows consumers to view reports in a mobile-optimized format.
64
Power BI Flow
Connect to data with Power BI Desktop, Transform data with Power Query Editor (comes with Power BI Desktop), Model data with Power BI Desktop, Create visualizations and reports with Power BI Desktop, Publish report to Power BI service, Distribute and manage reports in the Power BI service.
65
Power BI Building blocks
semantic models and visualizations
66
Semantic Models
consists of all connected data, transformations, relationships, and calculations
67
Visualizations
used to build pages in reports
68
Work Spaces
foundation of the Power BI service and the location where reports are published
69
App
simplified interface to access reports and dashboards
70
Template apps
allow you to find an existing app that suits your needs and then you connect your data.
71
Microsoft Fabric
A end-to-end analytics platform that provides a single integrated environment for data professionals and the business to collaborate on data projects and provides a set of integrated services that enable you to ingest
72
Services in Fabric
Data Engineering, Data Integration, Data Warehousing, Real-time intelligence, Data Science, and Business Intelligence
73
Copilot
generative AI assistant that enhances productivity across all workloads by providing intelligent code completion, natural language to SQL conversion, automated insights, and contextual assistance for data professionals and business users alike.
74
Software as a service
Platform where all data is stored in a single open format in OneLake
75
OneLake
Fabric's centralized data storage architecture that enables collaboration by eliminating the need to move or copy data between systems and unifies data into a single logical lake without moving or duplicating data
76
Azure Data Lake Services
where One Lake is built
77
Shortcuts
references to files or storage locations external to OneLake allowing you to access existing cloud data without copying it and consistency in data is maintained
78
Workspaces
serve as logical containers that help you organize and manage your data, reports, and other assets and provide a clear separation of resources, making it easier to control access and maintain security.
79
Admin Portal
Where fabric administration is centralized and you can manage groups and permissions, configure data sources and gateways, and monitor usage and performance
80
OneLake catalog
helps you analyze, monitor, and maintain data governance and provide guidance on sensitivity labels, item metadata, and data refresh status, offering insights into the governance status and actions for improvement
81
Data Engineers with Microsoft Fabric
can ingest, transform, and load data directly into OneLake using Pipelines, which automate workflows and support scheduling and store data in lakehouses, using the Delta-Parquet format for efficient storage and versioning.
82
Analytics Engineers with Microsoft Fabric
bridge the gap between data engineering and analysis by curating data assets in lakehouses, ensuring data quality, and enabling self-service analytics and create semantic models in Power BI to organize and present data effectively
83
Data Analysts with Microsoft Fabric
transform data upstream using dataflows and connect directly to OneLake with Direct Lake mode, reducing the need for downstream transformations and create interactive reports more efficiently using Power BI
84
Data Scientists with Fabric
use integrated notebooks with support for Python and Spark to build and test machine learning models and can store and access data in lakehouses and integrate with Azure Machine Learning to operationalize and deploy models.
85
Low to no code users with Fabric
discover curated datasets through the OneLake catalog and use Power BI templates to quickly create reports and dashboards and use dataflows to perform simple ETL tasks without relying on data engineers
86
Tenant Settings
Found in the admin portal and is where admins can enable Fabric
87
Workspace Settings Configurations
License type to use Fabric features, One Drive access for the workspace, Azure Data Lake Gen2 Storage connection, Git integration for version control, Spark workload settings for performance optimization
88
Data Engineering Fabric Workload
Create lakehouses and operationalize workflows to build, transform, and share your data estate
89
Data Factory Fabric Workload Ingest
Ingest, transform, and orchestrate data
90
Data Science Fabric Workload
Detect trends, identify outliers, and predict values using machine learning
91
Data Warehouse
Combine multiple sources in a traditional warehouse for analytics
92
Databases Fabric Workload
Create and manage databases with tools to insert, query, and extract data
93
Industry Solutions Fabric Workload
Use out-of-the-box industry data solutions
94
Real Time Intelligence Fabric Workload Process
Process, monitor, and analyze streaming data
95
Power BI
Create reports and dashboards to make data-driven decisions
96
Data Engineering & Data Science Copilot Capabilities
Intelligent code completion, automated routine tasks, industry-standard code templates, and contextual code suggestions that adapt to specific tasks and help with data preparation, pipeline building, and insight generation
97
Data Factory Copilot Capabilities
AI-enhanced tool set supporting both citizen and professional data wranglers with intelligent code generation for data transformation and code explanations for complex tasks
98
Data Warehouse and SQL Database Copilot Capabilities
Natural language to SQL conversion, code completion, quick actions, and intelligent insights
99
Power BI Copilot Capabilities
Automatic report generation, summary creation for report pages, synonym generation for better Q&A capabilities, and natural language querying of data. Business users can also use Copilot to extract more insights and chat with the report data
100
Real Time Intelligence Copilot Capabilities
Automatic report generation, summary creation for report pages, synonym generation for better Q&A capabilities, and natural language querying of data. Business users can also use Copilot to extract more insights and chat with the report data
101
Copilot with Power BI
AI-powered assistant that helps you work with data more efficiently and can be used to prepare semantic models and create reports
102
Steps for clean data in Power BI
Clean, Profile, and Transform
103
Profile Data
Assess column quality, distribution, and profile
104
Clean Data
Address missing values, correct out-of-range or inconsistent entries, and remove duplicates
105
Transform Data
Address missing values, correct out-of-range or inconsistent entries, and remove duplicates
106
Transform
Rename columns, set correct data types, and reshape tables as needed
107
Relationships
allow you to filter and summarize data in report visuals later in the development process
108
Autodetect Relationships Feature
allows you to automatically detect relationships so you can use copilot to summarize the initial semantic model
109
Power BI Desktop Views
Report, Table, Model, and DAX Query
110
DAX Query View
you can use copilot to describe what you want the query to do
111
Copilot Prompts
used to build interactive reports faster in Power BI
112
Prep Data for AI feature
Used to further curate the business user's experience and provide Copilot with the context it needs to reduce ambiguity and improve relevance and accuracy
113
Simplify the data schema
removing unnecessary tables and columns, and using clear, descriptive names
114
Verified Answers
associate common business questions with specific visuals
Microsoft Power BI
flashcards
Decks in class (10)
# Cards
-
Getting Started in Microsoft Data Analytics114
-
Getting Started in Microsoft Data Analytics Questions13
-
Prepare Data For Analysis in Power BI47
-
Prepare Data For Analysis With Power BI Questions9
-
Model Data With Power BI64
-
Model Data With Power BI Questions23
-
Design Effective Reports in Power BI74
-
Design Effective Reports in Power BI Questions14
-
Manage and Secure Power BI66
-
Manage and Secure Power BI Questions15
