Data visualization is an integral part of the data science and analytics process, but what do you need to know to get started? Is there a blueprint for data visualization What’s the Roadmap to Data Visualization Success?success that you can use? We’ve created a simple framework for achieving data visualization success built around processes and a leading-edge Qlik Sense extension.
Understand Current State
When establishing a roadmap to data visualization success, it’s essential to understand the current state of your data. Seek to know what you’re looking for and your unique business needs.
You’ll also want to know how your data looks now—it may consist of disparate sources, different formats, and varying degrees of quality. You can easily create a plan for merging or cleaning up these different sources to integrate them into a single platform.
On top of that, many other factors can affect how easy or difficult implementation is going to be:
- How much time and money do you have?
- What capabilities does your technology stack provide?
- How many people will you need on board?
- How much support will you need from teams outside your own organization?
Identifying the barriers to success is critical in creating effective data visualization. After all, if you don’t know your staff’s challenges, how can you help them overcome them?
Just as important as identifying the challenges themselves is understanding their root causes so you can address them directly.
Three main things get in the way of good data visualization:
A Lack of Understanding About What Makes for Effective Visualizations
Organizations need to understand what makes a good visual and how to communicate their insights through them effectively. While many think they know what makes an effective data visualization framework, they often lack the skills to create one.
It leads to frustration, wasted time and money, and ultimately no progress toward achieving their goals.
Difficulties Around Accessibility (Both Physical and Digital)
Your audience may not have access to your report or dashboard because they can’t get into your office. It could also be that they don’t have access to certain sites due to organization policy. Either way, you won’t see any benefit from creating the visualizations.
Data Quality Issues
Data quality is a common barrier to successful data visualization, especially when the data rests in multiple sources or formats. Without proper quality control and management, it can be difficult to ensure that data is ready for analysis and reporting. The lack of consistent terminology can also lead to poor data quality, as does incorrect naming conventions.
Develop Future State Vision
A critical preliminary step on the road to data visualization success is developing a vision for what you want to achieve with your visualizations. A clear vision will help you focus on creating the most useful and usable visualizations possible.
What do you want your users to be able to do or experience? Which are the key features that make this possible? Can you deliver these features using a Qlik sense extension?
How can you improve current processes to make them easier for people within your business unit (BU)? How do you enable external customers and partners to use them with minimal training?
What do you see when you think of data visualization and how it can help your business? A bar chart that shows revenue over time or a pie chart showing the growth of different products? Those are both good examples, but there are other ways to present information visually.
Use a Timeline Chart for Sequence
A timeline chart is a good option for showing the sequence of events. It’s also possible to use it to show timelines that are not in chronological order.
For example, if you have data points representing different products, you can use a timeline chart to compare the performance of these products over time. The advantage of this type of chart is that it allows users to quickly see how things change over time and their overall trend.
Show the Overall Picture
Bar charts are great at showing the overall picture. They are useful when comparing multiple options against each other (for example, which team won each game). You can also use bar charts to show how one option has changed over time (for example, how much money you spent on marketing during different periods).
Waterfall Chart Qlik Sense Extension
A waterfall chart is similar to a stacked bar chart, but instead of being grouped by one variable, each bar represents multiple values on multiple dimensions (usually time). These charts help you see the causes behind changes in metrics over time.
The Vizlib Waterfall chart is one of the most versatile and powerful chart types in Qlik Sense. It builds on the traditional waterfall chart, but it’s designed to be more flexible and easier to use.
The Vizlib Qlik Sense extension waterfall chart is an excellent choice when you need to show how values change over time, such as revenue or profit margin over time.
Annotate Your Charts
Charts should tell a story, but sometimes, they’re not clear enough because they lack context or explanation. That’s where annotations come into play.
An annotation is an explanatory note that appears directly on top of a chart element (or a table cell).
Annotations are useful because they give additional information about a value in the same place where people are looking at it: right next to the data point on the screen.
Provide Context for Your Data
Data visualizations are most effective when they provide context for the data. You can provide the context in several ways, including:
- Showing trend lines
- By comparing the data to previous reports
- By including a title or description to explain what the data means.
Understand Your Data
How much time do you have? Data analysis can be time-consuming, depending on what kind of information you’re working with. When working with large amounts of data or trying new methods such as neural networks or machine learning algorithms, more iterations will likely be required before results become usable.
At a minimum, though, there should always be some initial analysis done so that teams are ready when jumping into any new project involving data analytics tasks.
Develop an Implementation Plan
To further your data visualization success, you must have a strategy. A good strategy will allow you to make the most out of your time and money.
A road map is only as good as its implementation. In other words, it doesn’t matter if you know where you want to go if no one’s willing or able to follow through on getting there with you.
As such, it’s important that everyone involved in the project understands their job and that everyone does their job so that everything runs smoothly from start to finish. Here are useful tips for your implementation strategy:
It would help if you also clarified the scope of your project. Is this an initiative that will impact every department or just one? How many people will be involved, and what’s the budget?
If this is an enterprise-wide initiative, all stakeholders must be on board. They need to understand why data visualization is important and how it can help them achieve their goals.
It’s also critical that senior management supports the initiative by providing resources and funding so it doesn’t fall flat in its first few months.
There are plenty of free and paid tools that can help you build visualizations quickly and easily. The key is finding one that matches your needs as closely as possible while offering enough flexibility for customization when necessary.
Some platforms have better features than others — the Vizlib Qlik Sense extension is known for its intuitive interface and powerful analytics capabilities. At the same time, Power BI offers robust visualizations and interactive dashboards.
Keep It Simple
Use a single chart or dashboard. If you use multiple charts, ensure they all show the same data differently.
Use one type of chart (bar, line, pie). Don’t mix and match several types within a single visualization.
Use tables and maps. They are easy to read and understand, which is why they are valuable for business intelligence dashboards. Include appropriate legend labels that explain what each color or icon represents (such as red for low sales and green for high sales).
Let the Data Tell the Story
When creating data, visualizations allow the data to tell its own story. Choose a chart type or graph that allows you to see the data’s trends, patterns, and relationships.
For example, if your data represents sales figures, bar charts or line graphs will help show high and low points over time.
Suppose your data shows how many customers were served at each store location on a given day. In that case, pie charts will be most useful for showing the distribution of customer traffic across locations.
Visualize the Right Way
There’s no doubt that data visualization has made huge strides in recent years. To improve visualization success, first, define the business problem you are trying to solve to improve success and identify the data available for analysis. Visualize the data using tools like our Vizlib Qlik Sense extension and create KPIs. Implement the solution with stakeholders.
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