Final Exam: Systems Analyst

Final Exam: Systems Analyst

• analyze the detailed distribution of numeric values in a field by creating a violin plot in Plotly
• assemble the pieces required to construct a simple chart using Google Charts
• combine related plots into a single page using a dashboard in Plotly
• configure the axes of a plot to make them more prominent and make your charts easier to read
• constrain a child table from having any values in a column that are not in a specified column of the parent table using foreign key constraints
• convey details about geographical regions using an atlas map in Plotly
• convey hierarchical information in your data using a treemap visualization
• convey information related to countries by using a geo chart
• convey the relationship between two fields in your dataset using a scatter chart
• create and use an update trigger, which is executed after updates to a MariaDB table
• create a plot with two charts by rendering them within subplots
• customize the appearance and the data displayed in a Google chart
• define a Chart Studio table using data and formatting information set in a file
• define a column chart with multiple series stacked on top of one another to recognize their individual and aggregate impact
• demonstrate how Google Charts can be customized using several properties in an options object
• execute commands from the DBeaver environment
• illustrate the basic usage of the DISTINCT and GROUP BY keywords
• illustrate the different ways in which a data table can be created and populated using the DataTable class
• illustrate the various customizations available for a treemap
• install and launch DBeaver as a user interface for MariaDB on macOS
• install and launch DBeaver as a user interface for MariaDB on Microsoft Windows
• install and launch MariaDB on macOS, then connect to it from the terminal
• install and launch MariaDB on Microsoft Windows, then connect to it from the command prompt
• load one of the example charts in Chart Studio to recognize the features available to visualize data
• log in to the Plotly Chart Studio web console and create a new data grid
• merge related plots into a single page using a dashboard in Plotly
• override the default ON DELETE behavior of foreign key constraints in MariaDB tables to implement cascading delete
• perform basic cross and inner joins using SELECT-FROM-WHERE queries
• plot a material chart to visualize the same data viewed with a column chart
• plot locations on a map, which can include satellite, street, or terrain information
• plot the variations in the price of a tradeable asset using candlestick charts in Plotly
• portray the flow of data from a source to a destination using a Sankey chart
• recognize and use the BETWEEN, LIMIT, and ORDER BY keywords
• recognize different aggregate functions within GROUP BY queries and work with the HAVING clause to filter results of GROUP BY operations
• recognize how default ON DELETE behavior of foreign key constraints in MariaDB works and perform a three-way join
• recognize the different data formats that can be loaded into Chart Studio
• recognize what triggers are, implement an insert trigger, and observe its working mechanism
• render a pie chart to analyze the proportion of contributions from various categories
• render the data present in a file on Google Drive in a Google chart
• represent multiple dimensions of data in your scatter plot by configuring the points that are rendered
• run a few basic SELECT-FROM-WHERE queries
• set up a combo chart with multiple visualizations for the same data
• set up an interactive chart with control within a Google Charts dashboard
• share your Plotly Chart Studio plots
• share your Plotly Chart Studio plots and data with viewers and collaborators
• use a chart editor to enable users to pick the best chart to visualize a dataset
• use Plotly to render information about geographical regions by shading regions based on the value of a variable
• use Plotly to visualize the proportional contribution of various categories that have a hierarchical relationship
• use the Falcon client to integrate Chart Studio with the results of a query against a relational database
• use the following constraints: NOT, NULL, and UNIQUE
• use the JOIN keyword to perform cross joins, inner joins, left outer joins, and right outer joins
• use the LIKE, NOT LIKE, IN, and NOT IN keywords work
• Use the SOME, ALL and ANY keywords to link subqueries to outer queries
• use UNIQUE constraints in an in-depth and applied way
• View the distribution of values in a field by plotting a histogram
• view the relationship between two variables in your dataset by plotting them in a scatter plot
• visualize a series of data using an area chart
• visualize preexisting data in a Chart Studio data grid in the form of a bar chart
• visualize the distribution of numeric values in a field by rendering a box plot using Plotly
• visualize your data in the form of a column chart

Final Exam: Systems Analyst will test your knowledge and application of the topics presented throughout the Systems Analyst track of the Skillsoft Aspire Business Analyst to Data Analyst Journey.

Google Chart Tools: Advanced Visuals with Charts

Google Chart Tools: Advanced Visuals with Charts

• discover the key concepts covered in this course
• convey information related to countries by using a geo chart
• plot locations on a map which can include satellite, street, or terrain information
• portray the flow of data from a source to a destination using a Sankey chart
• convey hierarchical information in your data using a treemap visualization
• illustrate the various customizations available for a tree map
• plot a value that falls within a range using a gauge chart
• portray data for each day in a calendar year using a calendar chart
• summarize the key concepts covered in this course

Once you're familiar with the basics of Google Charts, you can build on this to create more exciting and advanced visualizations. In this course, you'll get hands-on experience with some of the specialized visuals available in Google Charts. You'll learn how to work with geo charts to convey information related to countries and map charts to convey data on satellite, street, and terrain maps.

You'll also work with Sankey charts to convey data flow, treemap charts to show hierarchical information, gauge charts for values within a range, and calendar charts for daily date-related data. In addition, you'll recognize what kind of data can be portrayed in these charts and learn how to set up and customize them.

Google Chart Tools: Basic Charts

Google Chart Tools: Basic Charts

• discover the key concepts covered in this course
• assemble the pieces required to construct a simple chart using Google Charts
• illustrate the different ways in which a data table can be created and populated using the DataTable class
• demonstrate how Google Charts can be customized using several properties in an options object
• customize the appearance and the data displayed in a Google chart
• visualize your data in the form of a column chart
• compare different series by rendering them alongside one another in a column chart
• configure column charts to convey precisely the information you would like your users to view
• define a column chart with multiple series stacked on top of one another to recognize their individual and aggregate impact
• plot a material chart to visualize the same data viewed with a column chart
• distinguish between the standard and material versions of Google charts
• set up a combo chart with multiple visualizations for the same data
• visualize a series of data using an area chart
• summarize the key concepts covered in this course

Google Charts provides a handy tool for developers who need to create standard and powerful charts for their users. In this course, you'll explore Google Charts through a series of labs in which you'll build several data visualization charts. You'll start with the very basics - the HTML and JavaScript components that you need to put together to render Google charts, such as the DataTable and options objects.

While doing so, you'll construct some of the fundamental charts available in the Google Charts library, such as pie, bar, and area charts. You'll then use various customization and visualization techniques, such as changing a chart's appearance and the data it shows and using stacked column charts, combo charts, material charts, and charts with dynamic behavior.

Google Chart Tools: Interacting with Charts

Google Chart Tools: Interacting with Charts

• discover the key concepts covered in this course
• render the data present in a file on Google Drive in a Google chart
• convey the relationship between two fields in your dataset using a scatter chart
• use a chart editor to enable users to pick the best chart to visualize a dataset
• recognize the various chart customizations available when using a chart editor
• set up an interactive chart with a control within a Google Charts dashboard
• design a dashboard containing multiple charts and multiple controls to define what data the charts should convey
• summarize the key concepts covered in this course

When developing charts with Google Charts, you can control not only what data your users see, but also how they interact with it. In this course, you'll explore the different ways in which user interaction with Google Charts can be set up and configured.

You'll start by learning how to get data from Google Drive and use it in your Google charts. You'll then learn how to convey the relationship between fields using a scatter chart. Next, you'll learn how to create a chart editor to allow users to choose the right chart for their data. You'll learn how to work with dashboards and controls to enable users to visualize a subset of their data dynamically. Lastly, you'll design a dashboard with multiple charts and controls.