The document provides an overview of a Power BI training course. The course objectives include learning about connecting to data sources, transforming data, building data model relationships, using DAX functions to transform data, and creating visualizations. It discusses topics like importing data from CSV and Excel files into Power BI, using Power Query to transform data, establishing relationships between tables in the data model, using measures and columns with DAX, and building basic and dynamic visualizations. It also provides resources for sample data files and additional learning materials for the course.
This document provides an introduction to Power BI, a business intelligence tool for data visualization. It discusses how Power BI helps organizations make more data-driven decisions by combining business analytics, data mining, visualization and infrastructure. Key features of Power BI include rich dashboards, report publishing, no constraints on memory or speed, and no need for technical support. Power BI consists of desktop, service and mobile app components and allows users to connect to data, model and format it, create visualizations, and publish reports.
This document provides an overview of the Power BI learning journey. It outlines the basic, intermediate, and advanced levels which include understanding Power Query, Power Pivot, DAX, Power View, and building reports in Power BI Desktop and the Power BI web/mobile apps. The three main stages are discover (with Power Query), analyze (with Power Pivot and DAX), and visualize (with Power View, Power Map, and Power BI tools). Understanding functions like CALCULATE, relationships, and measures is important for effective data modeling and dashboard creation in Power BI. Upcoming features and resources for continued learning are also mentioned.
What is Microsoft Power BI and what are its benefits. how we can Analyse data with the help of power BI. Power BI A Microsoft Business Intelligence and Data Analysis tool.
Power BI is a business analytics service that allows users to analyze data and share insights. It includes dashboards, reports, and datasets that can be viewed on mobile devices. Power BI integrates with various data sources and platforms like SQL Server, Azure, and Office 365. It provides self-service business intelligence capabilities for end users to explore and visualize data without assistance from IT departments.
Power BI is a business analytics service that enables you to see all of your data through a single pane of glass. Live Power BI dashboards and reports...
The slide deck from data and analytics workshop for HR professionals. Presented in @hrtechgroup event in Microsoft Vancouver. The workshop was built around the HR sample partner data set
https://docs.microsoft.com/en-us/power-bi/sample-human-resources
Business intelligence dashboards and data visualizations serve as a launching point for better business decision making. Learn how you can leverage Power BI to easily build reports and dashboards with interactive visualizations.
Power BI is a business analytics service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.
This presentation will give you an overview of what Microsoft Power BI is. What are its features. Why it is an upcoming popular Data Visualization tool in the market. How to use it and comparison with other Visualization tools.
BI: new of the buzz words that everyone is talking about but what is it? How can it be used to make a impact in my organization? How do I get started? In this session, we will talk about it and show you a live example in Office 365's SharePoint Online.
Objectives/Outcomes: In this session, participants will learn:
1. What is BI
2. What is Microsoft's Power BI
3. Case Studies
4. How can I get it
What is the Power BI and learn the Power BI by self and this presentation contains some use full links which help us at time of developing the Power BI.
Power BI is a collection of services from Microsoft used for modeling, analyzing, and visualizing data. It involves data modeling by organizing and preparing data, data visualization through interactive reports and visuals to develop business insights, and a workflow that includes connecting data sources, loading data into a data model, and building visualizations. The Power BI desktop application is used to create data models and reports which can then be saved locally.
Power BI Training | Getting Started with Power BI | Power BI Tutorial | Power...Edureka!
This Edureka tutorial on "Getting started with Power BI" will provide you the fundamental knowledge of Power BI. Below are the topics covered in this tutorial:
1. What is Self Service Business Intelligence?
2. Why Power BI?
3. What is Power BI?
4. Demo on Power BI
This document discusses the future of data and the Azure data ecosystem. It highlights that by 2025 there will be 175 zettabytes of data in the world and the average person will have over 5,000 digital interactions per day. It promotes Azure services like Power BI, Azure Synapse Analytics, Azure Data Factory and Azure Machine Learning for extracting value from data through analytics, visualization and machine learning. The document provides overviews of key Azure data and analytics services and how they fit together in an end-to-end data platform for business intelligence, artificial intelligence and continuous intelligence applications.
This slide deck explains in a comprehensive way what Power BI is, how the Power BI architecture looks like and what the usage scenarios are for using Power BI and related tools
The document introduces Power BI tools for self-service business intelligence including Excel add-ins like Power Query, PowerPivot, Power View, and Power Map. It also discusses Power BI for Office 365, the Power BI Preview, Power BI Designer, and the Power BI app. The presenter demonstrates these tools and provides resources for learning more.
What Is Power BI? | Introduction To Microsoft Power BI | Power BI Training | ...Edureka!
( Power BI Training - https://www.edureka.co/power-bi-training )
This Edureka "What Is Power BI?" tutorial will help you an introduction to Power BI. This video helps you to learn the following topics:
1. Why Power BI?
2. What Is Power BI?
3. Who Use Power BI?
4. Components Of Power BI
5. Building Blocks Of Power BI
Check out our Power BI Playlist: https://goo.gl/97sJv1
Microsoft Power BI | Brief Introduction | PPTSophia Smith
What is Power BI?
Microsoft Power BI is one of the most powerful data visualization software. It empowers the organizations with their tools and help the users to transform their raw data into valuable information. Let's have a look on How Power BI helps to your business.
This document provides an overview of a training on Microsoft Power BI. It introduces Power BI as a business intelligence tool consisting of three core applications: connecting to data sources, data preparation and analysis, and visualization and collaboration. It outlines the key topics that will be covered in the training, including connecting and transforming data in Power BI Desktop, data modeling, analyzing data with DAX calculations, visualizing and formatting data, filters, and refreshing and scheduling reports in Power BI Service. The training will cover the components and building blocks of Power BI, how to use the Power BI Desktop interface, and include hands-on exercises for working with data, creating reports and dashboards, and publishing to Power BI Service.
This document provides an overview of measures in Power BI Desktop and includes a tutorial for creating basic measures. It discusses automatic measures, creating measures using DAX functions, and common measure examples like sums, averages, and counts. The tutorial guides the reader through understanding measures and creating their own basic measures in the Power BI Desktop model.
Power bi slide share pdf it is a very importantSatyabratarath5
It is first pdf I am Satyabrata rath my 1st pdf in power bi it is most wonderful pdf .A basic knowledge in power bi
Power bi most wonderful pdf.power bi is business purposes tool
There are five types of datasets in Power BI: connected data models, uploaded Power BI Desktop files, Excel/CSV files, push datasets, and streaming datasets. Datasets represent data ready for reporting and visualization. Power BI can connect to external hosted models like SQL Server Analysis Services. Dataflows allow users to organize, clean, and transform data from multiple sources into a unified data structure for building datasets and reports. Dataflows use an Azure Data Lake for data storage while datasets point to subsets of dataflow data for specific reports.
Create a basic performance point dashboard epcEPC Group
This document provides instructions for creating a basic PerformancePoint dashboard with three key elements:
1) It describes creating a simple dashboard that contains a scorecard, an analytic grid report, and a filter.
2) It orients the user to the Dashboard Designer user interface which is divided into four main areas: the ribbon, workspace browser, center pane, and details pane.
3) It guides the user through creating the dashboard items - selecting a data source, creating an analytic grid report to display data from the source, selecting or creating KPIs, and then generating a scorecard and filter to populate the new dashboard.
Power BI is a collection of software and services that allows users to analyze unrelated sources of data and turn it into interactive visual reports. It includes the Power BI Desktop application, Power BI online service, and mobile apps. The common workflow in Power BI involves connecting data sources in Power BI Desktop, building a report, publishing it to the Power BI service, and sharing it so others can view and interact with the report.
Power BI desktop helps import data, transform data, visualize the data, and create reports, and these reports you can share with other people in your organization. Here are the steps to create a report in Power BI Desktop.
Tableau - Learning Objectives for Data, Graphs, Filters, Dashboards and Advan...Srinath Reddy
Step-1 Tableau Introduction
Step-2 Connecting to Data
Step-3 Building basic views
Step-4 Data manipulations and Calculated fields
Step-5 Tableau Dashboards
Step-6 Advanced Data Options
Step-7 Advanced graph Options
Power BI data modeling is the process of creating a relationship between common columns of multiple tables. If the column headings are the same across tables, then Power BI auto-detects the relationship between tables. Using these columns, we can merge the tables as well.
This document provides answers to common interview questions about Tableau. It discusses the differences between .twb and .twbx file extensions, how to join and blend data, how to create calculated fields and sets, and how to schedule automated report refreshes. It also covers topics like shelves, groups, hierarchies, extracts, performance testing, and stories. The document aims to equip job candidates with knowledge of Tableau's core functionality and capabilities.
This document is part of Oracle BI Publisher Certification Program from Adiva Consulting Inc. contact
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BI Publisher 11g : Data Model Design documentadivasoft
This document is part of BI Publisher 11g Training program from Adiva Consulting Inc.
Contact info@adivaconsulting.com any Corporate Training need and save 75% of your training budget.
process that manages the data extracts and caches them in
memory for fast access.
Tableau
26
Architecture
Gateway / Load balancer: distributes requests from clients to application
servers. It provides high availability and scalability.
Customers: Tableau offers desktop, web and mobile clients to access
Tableau Server.
- Tableau Desktop: allows you to create and edit visualizations and
dashboards.
- Web interface: allows you to view and interact with published views.
- Tableau Mobile: optimized for mobile devices to view and interact with
published views.
Tableau
27
Technical Review
Tableau
28
Technical Review
Data Connectivity
- Connects to a
As a leading data visualization tool Tableau has many desirable and unique features. Its powerful data discovery and exploration application allows you to answer important questions in seconds. You can use Tableau's drag and drop interface to visualize any data, explore different views, and even combine multiple databases together easily. It does not need any complex scripting. Anyone who understands the business problem can address it with a visualization of the relevant data. When the analysis is finished, sharing with others is as easy as publishing to Tableau Server.
Tableau allows users to create dashboards that display multiple worksheets and views together for easy comparison of data. To create a dashboard, select Dashboard > New Dashboard from the menu. Views and objects can then be added and arranged on the dashboard. Parameters and filters can be used to make dashboards interactive and allow users to dynamically change the data displayed. Maintaining good performance in Tableau requires limiting the amount of data pulled into views through appropriate filtering and aggregation of data.
The document outlines a 6-step process for database design using MySQL:
1. Define the purpose of the database and applications that will use it.
2. Determine the necessary tables to organize information.
3. Determine the fields for each table to store desired information and choose data types.
4. Determine relationships between tables by identifying which fields relate to primary keys in other tables.
5. Create a diagram of the database schema using software.
6. Refine the design if needed by reviewing for any additions, changes, or errors.
This document outlines the topics covered in various units of a database course, including query basics, joins, forms and reports design, transactions, data storage methods, and distributed applications. Key concepts discussed are form and report layout, creating forms and reports, graphical objects, PL/SQL, triggers, error handling, application structure, and table operations. Data storage methods covered include sequential storage, pointers, indexes, linked lists, B-trees, hash tables, and centralized vs distributed storage models like RAID.
Smart View is a Microsoft Excel add-in that allows users to connect to and analyze financial data from within Excel. It provides tools to connect to data sources, view and manipulate data using familiar Excel functions and formulas, and submit data back to the source system. Key capabilities include ad hoc analysis of retrieved data, pivoting and drilling into dimension hierarchies, and creating functions to exchange data between Excel and the source application.
Towards an Analysis-Ready, Cloud-Optimised service for FAIR fusion dataSamuel Jackson
We present our work to improve data accessibility and performance for data-intensive tasks within the fusion research community. Our primary goal is to develop services that facilitate efficient access for data-intensive applications while ensuring compliance with FAIR principles [1], as well as adoption of interoperable tools, methods and standards.
The major outcome of our work is the successful creation and deployment of a data service for the MAST (Mega Ampere Spherical Tokamak) experiment [2], leading to substantial enhancements in data discoverability, accessibility, and overall data retrieval performance, particularly in scenarios involving large-scale data access. Our work follows the principles of Analysis-Ready, Cloud Optimised (ARCO) data [3] by using cloud optimised data formats for fusion data.
Our system consists of a query-able metadata catalogue, complemented with an object storage system for publicly serving data from the MAST experiment. We will show how our solution integrates with the Pandata stack [4] to enable data analysis and processing at scales that would have previously been intractable, paving the way for data-intensive workflows running routinely with minimal pre-processing on the part of the researcher. By using a cloud-optimised file format such as zarr [5] we can enable interactive data analysis and visualisation while avoiding large data transfers. Our solution integrates with common python data analysis libraries for large, complex scientific data such as xarray [6] for complex data structures and dask [7] for parallel computation and lazily working with larger that memory datasets.
The incorporation of these technologies is vital for advancing simulation, design, and enabling emerging technologies like machine learning and foundation models, all of which rely on efficient access to extensive repositories of high-quality data. Relying on the FAIR guiding principles for data stewardship not only enhances data findability, accessibility, and reusability, but also fosters international cooperation on the interoperability of data and tools, driving fusion research into new realms and ensuring its relevance in an era characterised by advanced technologies in data science.
[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016) https://doi.org/10.1038/sdata.2016.18
[2] M Cox, The Mega Amp Spherical Tokamak, Fusion Engineering and Design, Volume 46, Issues 2–4, 1999, Pages 397-404, ISSN 0920-3796, https://doi.org/10.1016/S0920-3796(99)00031-9
[3] Stern, Charles, et al. "Pangeo forge: crowdsourcing analysis-ready, cloud optimized data production." Frontiers in Climate 3 (2022): 782909.
[4] Bednar, James A., and Martin Durant. "The Pandata Scalable Open-Source Analysis Stack." (2023).
[5] Alistair Miles (2024) ‘zarr-developers/zarr-python: v2.17.1’. Zenodo. doi: 10.5281/zenodo.10790679
[6] Hoyer, S. & Hamman, J., (20
Introduction to Data Science
1.1 What is Data Science, importance of data science,
1.2 Big data and data Science, the current Scenario,
1.3 Industry Perspective Types of Data: Structured vs. Unstructured Data,
1.4 Quantitative vs. Categorical Data,
1.5 Big Data vs. Little Data, Data science process
1.6 Role of Data Scientist
DESIGN AND DEVELOPMENT OF AUTO OXYGEN CONCENTRATOR WITH SOS ALERT FOR HIKING ...JeevanKp7
Long-term oxygen therapy (LTOT) and novel techniques of evaluating treatment efficacy have enhanced the quality of life and decreased healthcare expenses for COPD patients.
The cost of a pulmonary blood gas test is comparable to the cost of two days of oxygen therapy and the cost of a hospital stay is equivalent to the cost of one month of oxygen therapy, long-term oxygen therapy (LTOT) is a cost-effective technique of treating this disease.
A small number of clinical investigations on LTOT have shown that it improves the quality of life of COPD patients by reducing the loss of their respiratory capacity. A study of 8487 Danish patients found that LTOT for 1524 hours per day extended life expectancy from 1.07 to 1.40 years.
Big Data and Analytics Shaping the future of PaymentsRuchiRathor2
The payments industry is experiencing a data-driven revolution powered by big data and analytics.
Here's a glimpse into 5 ways this dynamic duo is transforming how we pay.
In essence, big data and analytics are playing a pivotal role in building a future filled with faster, more secure, and convenient payment methods for everyone.
Annex K RBF's The World Game pdf documentSteven McGee
Signals & Telemetry Annex K for RBF's The World Game / Trade Federations / USPTO 13/573,002 Heart Beacon Cycle Time - Space Time Chain meters, metrics, standards. Adaptive Procedural template framework structured data derived from DoD / NATO's system of systems engineering tech framework
2. Learning Objectives
1. Overview of PowerBI
2. Connecting to data Sources
○ Extract data from CSV and Excel (xlsx)
○ Transform data using Power Query
○ Extend knowledge of Power Query tools
3. Modelling the Data- Relationships
○ Build data table model relationships
4. Dax functions in Power BI
○ Transform data using DAX formula
○ Measures and Columns
5. Creating Visualizations
○ Building Basic Visuals
○ Dynamic Page navigation
Understand the basics of Power BI, including the different
components of the tool and how they work together:
3. Overview of PowerBI
Power BI is a Business Intelligence tool developed by Microsoft. It helps you interactively visualize your
data and make intelligence-based business decisions as a result.
Key features of Power BI:
• Quick set up comparative to traditional BI
• Interactive visualizations
• Supports different data sources (Microsoft or otherwise)
• The ability to publish to web (app.powerbi.com)
• Cloud-based, no on-premise infrastructure needed
• Scalable
• Accessibility - view the dashboards/reports on iPad, iPhone,
Android, and Windows
devices Scheduled data refresh
4. Training Resources data files
For this Beginners training course in Power BI, we will base the learning
activities on several data files. Please create a new folder on your desktop
and download the data files in their current format (csv or xlsx):
1. Data file: data set > link
Microsoft Power BI Desktop is built for the analyst. It combines
state-of-the-art interactive visualizations, with industry-leading data query and
modeling built-in. Create and publish your reports to Power BI. Power BI
Desktop helps you empower others with timely critical insights, anytime,
anywhere.
To download use this link click download and select the option that is
compatible with your system.
6. Exploring the data files
Tables Description
DimCustomer Master data for customers
DimDate Master data for Date
DimProduct Master data for Products
DimProductCategory Master data for Product Categories
DimProductSubCategory Master data for Product Subcategories
FactinternetSales Transactional Data for all sales
Note: All the Sales level data rolls up to the customer data rows per transaction.
Data 1: Customer’s sales orders
7. Connecting to Data Sources
This process is followed at the start of a new project, to import the data that you’ll be working with, and at
any point in the future when you need to add new data to the project.
Open PowerBI from your local system • When you launch Power BI Desktop, a welcome splash screen
is displayed.
• To connect to the sample data for this exercise, select Get
Data on the left-hand
menu of the splash screen or from the home ribbon.
8. Connecting To Data Sources
• You can connect to the data source from that screen, and you can go to the
PowerBI environment.
• On the environment, you can get from the 4 sources on your page or click
on Get Data as shown below for more options.
• Select Text/CSV from the list and click Connect.
• Browse to the unzipped data files you saved in step 3.2, select the
first file DimCustomer.csv, and click Open
9. Connecting To Data Sources
• When you click Open, the below window appears, displaying sample data
from the selected file.
• Repeat the same process and load all other sample files (DimDate,
FactInternetSales, DimProduct, DimProductCategory, and
DimProductSubCategory).
Note that you will have to load these one at a time.
• At this point it would be useful to Save the Power BI Desktop
model.
The data has now been loaded into the Power BI model and you
have a blank canvas to start working with
Above, you can see the options Load and Transform Data. For now, click Load to
import the data directly into Power BI. This imports the data as it is, and loads it
into Power BI Desktop.
10. Interface Of Query Editor
• Query Editor consists of 4 Parts
1.Query Ribbon
2.Left Pane
3.Center (Data) Pane
4.Query Settings
The Ribbon in Query Editor consists of four tabs
• Home
• Transform
• Add Column
• View
Home Tab: The Home tab contains the common query tasks, including the first
step in any query, which is Get Data.
Transform: The Transform tab provides access to common data transformation
tasks, such as adding or removing columns, changing data types, splitting
columns, and other data-driven tasks.
Add Column: This tab provides additional tasks associated with adding a
column, formatting column data, and adding custom columns. The following
image shows the Add Column tab.
11. The PowerBI Desktop Application Interface
1. The left menu is used to switch
between, Report Design, Data
Transformations and Data
Modelling (creating relationships
within your data).
2. The Report Canvas is for Visual
Design and Layout.
3. The Application ribbons contain
all options and settings, visual or
page level properties, and another
settings configuration.
4. The report building panes contain
all the components that may be
added to a
report. You can:
a. Select fields and data from
imported tables on the Data
pane.
b. Select different ways to
display this data from the
Visualizations pane.
c. Apply filtering to the data in
the Filters pane.
Report Design,
Data Transformation and
Data Modeling Views
Report Canvas
Application Ribbons
Data Pane
Visualization
Pane
Page Tabs
Filter Pane
13. Creating Relationships
Once the required data is loaded, there may be a need to use Power Query
Editor to shape the data by removing unnecessary columns, changing data
types, adding new calculated columns, and so on. Power Query Editor is not
covered further in this document.
Power BI Desktop makes creating
relationships easy through an Auto
Detect feature. When the data is
loaded, Power BI Desktop will
attempt to find and create
relationships for you based on
column names in the tables. If there
are matching column names, these
relationships are created
automatically
• Select the Data Modeling view, as indicated below
It is worth noting the following details about relationships:
1. Relationship: The line between two tables represents that a relationship
exists.
2. Direction: The arrow indicates which direction filtering will occur. In this
example: If DimProduct is filtered on a particular value, FactInternetSales
will also be filtered to only show records related to the selected value.
3. “One” side: The 1 indicates that the relationship works off a single unique
record on the DimProduct table.
4. “Many” side: The * indicates that the relationship links to many records
on the FactInternetSales table
14. Creating Relationships
As not all relationships have been auto detected, we will need create the
rest of them manually.
The next section explains how we will do this.
• Select New…
• Select DimProduct from the first dropdown box
• Highlight the column ProductSubCategoryKey
• Select DimProductSubCateogory from the
second dropdown box
• Highlight the column ProductSubCategoryKey
• Select Modeling from the top menu. Then select Manage Relationships
• Ensure the Cardinality is set to Many to One (*:1), Cross filter
direction is set to single and “Make this relationship active” is ticked.
• Click Ok
• Click Close to save the relationships.
• Save the model
16. Data Analytics Expression
What is DAX?
DAX is the abbreviated form of Data Analytics Expressions (DAX). It means
that it is a type of formulae or expressions that are used for the analysis
and calculations of data in Power Query and Power BI. The combination or
collection of different expressions such as constants, operators, and
functions form a formula to give results or output. Power BI DAX helps in
finding more detailed information from raw data.
How does DAX work?
• There are three fundamental concepts for Power BI DAX: Syntax, Context,
and Functions.
Syntax
The Syntax comprises various components that make up a formula and how it’s
written. Look at this simple DAX formula
When is DAX used?
When a new column calculation is needed
When you create a data model on the Power BI Desktop, you can extend a
table by creating new columns. The content of the columns is defined by a
DAX expression, evaluated row by row or in the context of the current row
across that table.
Measures
There is another way of defining calculations in a DAX model, useful if you
need to operate on aggregate values instead of on a row-by-row basis. These
calculations are called measures. One of the requirements of DAX is that a
measure needs to be defined in a table. However, the measure does not
really belong to the table. So, you can move a measure from one table to
another one without losing its functionality. Measure, unlike Columns exist in
the filter context of the data.
Note
A column takes up physical space in your Power BI model, whereas a measure
is calculated and thus only evaluated when needed.
I. Total Sales is the measure name.
II. The equals sign operator (=) indicates the beginning of the formula.
III. SUM adds up all the numbers in the column, Sales[SalesAmount].
IV. There are these parentheses () that surround an expression
containing one or more arguments.
All functions require at least one argument.
V. Sales is the table referenced.
VI. An argument passes a value to a function. The referenced column
[SalesAmount] is an argument
with which the SUM function knows the column on which it has to
aggregate a SUM.
17. Data Analytics Expression
Functions.
Functions are predefined, structured and ordered formulae. They perform
calculations using arguments passed on to them. These arguments can be
numbers, text, logical values or other functions.
Aggregate Functions
MIN(<Column>), MAX(<Column>), SUM(<Column>), AVERAGE(<Column>)
COUNT Functions
DISTINCTCOUNT(<Column>), COUNT(<Column>), COUNTA(<Column>),
COUNTROWS(<Column>), COUNTBLANK(<Column>),
DATE-TIME Functions
DATE(<Year>,<month>,<day>),
HOUR(<Column>),TODAY(),EOMONTH(<Start_date>,<months>),Calendar(<StartD
ate>,<EndDate>)
Naming convention
18. Data Analytics Expression
DAX functions and operators that can be combined to build formulas and
expressions in a more effective way.
Remember: DAX formulas always start with an equal sign (=). You can
provide any expression that evaluates to a scalar, or an expression that can
be converted to a scalar after the equals sign.
Month To Date Sales
• Month-to-date (MTD): a period starting at the beginning of the current
calendar month and ending at the current date.
• Month-to-date is used in various contexts, typically for recording results of an
activity in the time between a date (exclusive since this day may not yet be
"complete") and the beginning of the current month.
• Example: If today is the 15th of the month, and your manager asks you for
the month to date sales figures, you will want to add your sales from the 1st of
the month up to the 14th (as the 15th is not complete yet).
19. Data Analytics Expression
Adding a Time Intelligence Quick Measure
DAX functions and operators that can be combined to build formulas and
expressions in a more effective way.
Month To Date Sales
• Month-to-date (MTD): a period starting at the beginning of the current
calendar month and ending at the current date.
• Month-to-date is used in various contexts, typically for recording results of an
activity in the time between a date (exclusive since this day may not yet be
"complete") and the beginning of the current month.
• Example: If today is the 15th of the month, and your manager asks you for
the month to date sales figures, you will want to add your sales from the 1st of
the month up to the 14th (as the 15th is not complete yet).
21. Principles of report design
Layout
● Alignment
● Order
● Proximity
● Space
● Sorting
● No clutter
Clarity
● Someone without prior knowledge
can understand the report without
any explanation
● Focus on most important element
● Change ‘left-right and top-down’ by
adding cues like labels, shapes,
borders, size, and colour
Aesthetics
● Meet a business need
● Some ‘beauty’ is required -
emotions kick in first!
● Create a theme or look
● Support, don’t detract
● Apply best practices