Data_Visualization_and_BI_Tool_vswgz1.pdf

data visualization

1. The Ultimate 

Guide to Selecting a
Data Visualization
and BI Tool

2. Table Of Contents
The Ultimate Guide to Selecting a Data Visualization and BI Tool 00Introduction 1
Benefits of Data Visualisation 1
Need for Real-Time Data Streaming
#1: Analyzing the Data in a Better Way
#2: Faster Decision Making
#3: Making Sense of Complicated Data 1
1
2
Steps for Data Visualization 2
Best Data Visualisation Tools
#1: Tableau
#2: IBM Cognos Analytics
#3: Microsoft Power BI 3
3
4
Factors to Consider While Selecting Data Visualisation Tools 4
Conclusion 6
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3. Introduction
The human brain is designed so that it can perceive visual information way faster than
numerical text information. There is a famous quote - “A picture tells a thousand words”
which is true to the core. A study shows that the human brain processes images 60,000
times faster than binary information and hence gains a lot more insights.
The recent studies on the impact of Data Visualization show that visual aids are 30 times
more informative. There has been a trend of Visualizing and gaining insights from data to
dive the companies forward. The trend shows that the companies that implement higher
levels of analytical aids are Twice more likely to be in the top quartile of financial
performance within their industries. Data Visualisation also decreases the time taken to
make decisions by up to 5 times. These figures show the importance of Data Visualisation
and the upper hand it provides.
The Ultimate Guide to Selecting a Data Visualization and BI Tool 01Benefits of Data Visualisation
Here are some of the most common benefits of Data Visualization:
1) Analyzing the Data in a Better Way
Analyzing reports helps business stakeholders focus on the areas that require attention. The
visual mediums help analysts understand the key points needed for their business. Whether
a sales report or a marketing strategy, a visual representation of data helps companies
increase their profits through better analysis and better business decisions.
2) Faster Decision Making
Humans process visuals better than any tedious tabular forms or reports. If the data
communicates well, decision-makers can quickly take action based on the new data insights,
accelerating decision-making and business growth.

4. The Ultimate Guide to Selecting a Data Visualization and BI Tool 02
3) Making Sense of Complicated Data
Data visualization allows business users to gain insight into their vast amounts of data. It
benefits them to recognize new patterns and errors in the data. Making sense of these
patterns helps the users pay attention to areas that indicate red flags or progress. This
process, in turn, drives the business ahead. Steps for Data Visualization
The following steps are necessary to achieve Data Visualization:
1) Develop your Research Question
It is vital to have a clear understanding of the goal of your research. This will determine what
sort of data is needed, the type of analysis necessary, and the types of visualizations that
would most effectively communicate your explorations or findings.
2) Get or Create your Data
Businesses utilize the data generated from various sources that they use for promotional
purposes and market understanding.
3) Clean your Data
This is an essential step to perform before creating a visualization. Clean, consistent data will
be much easier to visualize. Clean data is data that is free of errors or anomalies, making it
hard to use or analyze the data. Starting from a clean dataset allows you to focus on creating
an effective visualization rather than diagnosing and fixing issues while creating
visualizations.
4) Choose a Chart Type
It is essential to pick a chart or graph which will best communicate the message you wish to
tell your audience. The first step to choosing a chart is to determine what message you’re
trying to deliver.
5) Choose your Tool
Many tools to choose from, ranging from freely available open web-based tools to licensed
desktop tools.

5. The Ultimate Guide to Selecting a Data Visualization and BI Tool 03
6) Prepare Data
The data preparation steps you’ll need to go through are determined by the type of chart or
visualization you’d like to create and the tool which you have chosen. Once you’ve selected
your chart, you may need to perform transformations to retrieve the required data.
7) Create a Chart
Following the procedures specific to your tool, the general process for creating charts
includes:
Import data into the software.
Select the chart type you wish to create.
Evaluate the effectiveness of the chart.Best Data Visualisation Tools
The following tools are most popular for Data Visualization:
1) Tableau
Tableau is a data visualization tool that allows data analysts, scientists, statisticians, etc. to
visualize the data and get a clear opinion based on the data analysis. Tableau is very famous
as it can take in data and produce the required visualization output concisely. And it can do
this while providing the highest level of security with a guarantee to handle security issues as
soon as they arise or are found by users. Tableau also allows its users to prepare, clean, and
format their data and then create data visualizations to obtain actionable insights shared with
other users.
2) IBM Cognos Analytics
IBM Cognos Analytics is an Artificial Intelligence-based business intelligence platform that
supports data analytics, among other things. You can visualize as well as analyze your data
and share actionable insights with anyone in your organization. Even if you have limited or
no knowledge about data analytics, you can use IBM Cognos Analytics easily as it interprets
the data for you and presents you with actionable insights in plain language.

6. The Ultimate Guide to Selecting a Data Visualization and BI Tool 04
3) Microsoft Power BI
Microsoft Power BI is a Data Visualization platform focused on creating a data-driven
business intelligence culture in all companies today. To fulfill this, it offers self-service
analytics tools that can analyze, aggregate, and share the data in a meaningful fashion.
You must consider the following factors while choosing the required Data Visualization tool:
1) Chart Types for Business Needs
Data visualization tools compete on the breadth and variety of their chart types and the
flexibility of their configuration. If your organization wants to make extensive use of box and
whisker plots, make sure the tool has this chart type and can be used in the ways the
organization requires.
2) Layout Capabilities and Device Compatibility
When you embed a visualization, you need to review how it fits and interacts within the
layout(s) of your application. The visualization should take advantage of the entire screen
and responsively adjust for mobile device layouts.
3) Easy to Integrate
Review whether the platform’s approaches to embedding analytics into applications meet
business needs and are easy to implement. There should be simple embed codes to drop
the visualization into HTML for easy integration, but you should also review the APIs in case
additional flexibility is required.
4) Extend the Platform with Interactivity and Workflow
After embedding a visualization, verify whether it meets business requirements. In addition
to checking functionality built into the platform, like changing sort orders, selecting the
metrics used in visualizations, choosing which columns to display in a table, or switching
between chart types, you’ll want to verify you can extend the platform’s functionality in the
ways that you need, especially if you want users to update the underlying data.Factors to Consider While
Selecting Data Visualisation Tools

7. The Ultimate Guide to Selecting a Data Visualization and BI Tool 05
5) Security Configurable for the Required End-User
If you are building applications where different groups and users need access to various
data views, review how the platform enables row-level and column-level security. Verify that
the user login can trigger the data entitlements and that visualizations adjust for the
accessible data properly. You also want to see whether the platform has admin-level tools to
review visualizations as different users and validate whether visualizations reflect the proper
data entitlements.
6) Visualizations Perform Fast Enough to be Embedded in an Application
Depending on how end-users leverage the visualizations in analysis and workflow,
performance expectations vary. When a user of a BI application accesses a data
visualization, there is typically a higher tolerance for latency because the users are more
sensitized to the quantity of data and the complexity of the analytics.
7) Real-time Data Requirements
Related to performance is whether the platform enables real-time access to data sources or
whether computing analytics on cached or aggregated data is sufficient. There’s often a
trade-off between real-time data availability, performance, and implementation complexity, so
having the controls to switch from real-time to scheduled updates and validating
performance are required for larger data sets.
8) Development Capabilities That are Flexible and Scalable
When you incorporate embedded analytics in an application development cycle, you want to
ensure the embedded analytics platform fits your requirements for version control,
development, deploying workflow, testing practices, and continuous integration.
9) Platform’s Pricing and Total Cost
Most data visualization platforms have upfront costs and per-user charges. If you’re going to
embed a visualization and provide access to thousands of users, make sure the pricing and
costs are aligned with the application’s usage model. Modeling the costs is particularly
important when visualizations are embedded in customer-facing applications. The data
visualization platform’s per-user charge could amount to a significant percentage of your
total expenses.

8. The Ultimate Guide to Selecting a Data Visualization and BI Tool 06
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Book a demoConclusion
This guide provides comprehensive information regarding the concepts of Data
Visualization and the benefits of performing Visualisation business Data. There are loads
of Visualisation tools present in the market, and the factors mentioned above help in
choosing the best tools based on the requirements.