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Do you want to learn & get a job in Data Science?
The world is completely running on data; facts and figures have now become an integral part of every organization’s life. It’s more important than ever to have easily accessible ways to view and understand data. After all, the demand for data science skills in company professionals has been steadily increasing every year. Employees and business owners at every level should have a proper understanding of data and its growing impact. This is where data visualizations come into the picture. Data visualization is in the form of dashboards and go-to tools for many businesses that help to analyze and share information. It has the goal to make data more accessible and understandable. Data Visualization is a great tactic to enhance your data storytelling. Companies need impressive and convincing solutions for their problems. And data storytelling is a great form to deliver optimum results.
Data Storytelling is the art of driving insights from BIG Datasets with the help of analysis and making them presentable through data visualization. It will not only help capture valuable insights but even make content visually appealing and presentable so that clients can make appropriate data-driven decisions. With data science storytelling, you will be able to influence and inform your target audience based on your data analysis. It’s the best way to convey your message to them.
There are three essential elements of data storytelling:
Data – You analyze to build the foundation of your data story. This can be descriptive, predictive, or prescriptive, diagnostic analysis to help get a clearer picture
Narrative – This is a storyline, and the report is used to communicate insights gained from varied data analysis
Visualization – It will help communicate the story in a clear and impressive way – mostly numbers, graphs, charts, and audio-visuals speak for the potential data
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Simple! It helps in robust and focused decision-making. But here are some of the benefits of effective data storytelling.
•It helps in adding value to your data and insights
•Interpret complex information & highlight essential points for the target audience
•It gives a human touch to your raw but highly potential data
•It offers value to your target audience and industry
•It helps in building credibility in the market for the company
For instance, Airlines use data storytelling to help passengers find the preferred flights at the most economical prices and also for hosts to set up flight tickets at the most lucrative price band.
Data storytelling helps Airlines deliver personalized experiences and the best recommendations. Their price point feature will be constantly updated which will help guide hosts on how likely they are to get a booking at the customer’s chosen price. Other features include a host or guest interactions, social or festive events, and local market history in real-time which is available through the mobile app.
Now that we have a good understanding of data storytelling, let’s talk about how brand storytelling will work. Data analytic storytelling is when the company will use research, studies, and data analysis to share information about your brand and tell a lucrative story to consumers. It will turn complex datasets into meaningful and insightful easy to understand visually complex stories. It is different than creative storytelling in which the brand focuses on creating a perception while in data driven storytelling, the story will be based on factual data. Storytelling is a wonderful way to create brand awareness and connect with the potential audience. Data driven storytelling uses data visualization techniques that will grab attention.
Learn how to create and execute data visualization and tell an eye-catching story with your data by enrolling in Ekeeda Advanced Data Science Program. Learn Power BI storytelling today!
Studies show that our brain captures images faster than words and 90% of the information transmitted to the brain is visual in nature. We’re 65% more likely to retain visual information rather than theoretical representation. That’s why infographics, charts, and images are so powerful in conveying messages and brand recall.
For instance – In a bid to attract Millennials and steer away from their 'outdated' image, Chevrolet launched the #BestDayEver Campaign On April Fool’s Day. The campaign was a huge success, with the #BestDayEver hashtag generating some 1.5 billion social media impressions, while 3 million people viewed YouTube live stream and 75% of the engagement came from people younger than 35. This turned into an enormous amount of data into visually friendly info-graphic that car consumers can interpret with just a glance.
Today, the world is cluttered with cables of advertising and paid promotional content. To make the content stand out from competitors, you will need to have good visualization and a story that justifies it. Storytelling will help assign meaning and context to data that will otherwise look very ordinary, complex, and uninterested. Customers will gain proper clarity and better understanding and will tend to promote if it makes sense to them. Data storytelling will help extract and communicate valuable insights that will help you design strategies and offer & an intricate your customer’s buying journey. The content could be at any stage of the customer’s buying journey or even other than the sales cycle. Data storytelling will help create engaging & memorable marketing content that will help your brand grow and recall in consumer minds.
Learn how to use data visualization and storytelling in real-life instances to bring your story alive with the best data science course online!
Now that we have a good understanding of the brand’s data storytelling, let's begin to craft a story and the important steps in it To craft a compelling story, the most important element in building a story is the ‘Right narration’. You need an appealing story for it. There are four important elements to deliver a compelling story:
Characters – These are your key players or stakeholders in the story. They will be customers, suppliers, competitors, government, environmental, or any other form of group that is directly or indirectly related to your brand.
Settings – This is where you will use your data to reinforce the story narration. Whether an improved version of your product or service will increase safety or manufacturing process that impacts the environment. This is the ideal stage where you define the environment that concerns the clients and stakeholders.
Conflicts – Over here you will describe the root cause or issue you are trying to solve through data. It could be marketing content that will generate sales revenue, or you want your content team to deliver some good content for the sales team. Conflict will play a crucial role in making your story quite engaging and important. There has to be a problem for a data-driven solution.
Resolutions – Finally, you will propose a good solution for the identified issues. You will give short-term solutions with a long-term idea based on the problem type you would be solving. At this stage, your marketing outreach will be consistent and prominent, with visible messages across various channels. Your story should be a simple and direct solution to the issue. Whatever resolution or result you’ve achieved through data analysis, it should clearly indicate supportive facts and figures and compelling data visualization to make the story come alive and rescue operators. Your data storytelling should have all these steps to deliver your messages effectively to the potential audience.
Thus, with these steps, your potential audience will go through a compelling and engaging data story that will intrigue them to take necessary actions or steps to come up with business output and meet customers’ needs. This will be contributing to the overall business success and help achieve targets on time.
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Our brains are receptive to stories or visuals. Intriguing ones! Storytelling is not something new – from paintings to symbolic languages or codes, everything has a story attached to it. This world is in fact an amazing story. That’s the reason it resonates quite well in today’s fast-paced customer environment. Whether is infographics or videos, pictures or GIFs everything has a fascinating story incorporated in it.
Brands use storytelling based on factual data to drive the audience, create positive associations & finally encourage them to take desired actions. The best way to come up with a story narrative is to use internal data, be true, and share success stories and insights driven by your research & analysis. Then you can translate such insights into wonderful stories and visuals to brand recall and customer retentionships. Data Science is very important to come up with business strategies and make a remarkable change to business practices. Today, data scientists are regarded as a top-ranking profession in any analytics company. In fact, Glassdoor ranked Data Science as the top 3 career choices for the aspirants. Data Science means using scientific methods, processes, algorithms, and systems to extract insights from data, and then leverage the data to draw conclusions – in the form of decision-making, risk calculation, and targeting the audience to find market gaps and opportunities.
Ekeeda comes up with an exclusive Data Science course online for students and young professionals. There will be 1:1 live mentorship; wherein you can get in touch with industry professionals, and build a customized learning path for your data science career needs! Certification is easy but enlightening your path with knowledge and in-demand skills is the need of the hour!
This data science course online offers hands-on exposure to key data science technologies such as R, Python essential for ML, Deep learning, MLOps, and Stats for ML, through live interaction with world-class data practitioners, practical labs, and industry-aligned projects. What’s more? 100+ assignments and capstones, and placement assistance in top techs and start-ups such as Datascope, Tiger Analytics, Cloudera, Innofied, Konstant Infosolutions, Colan Infotech, December Labs, BCG Gamma, Brainvire, Palantir, Addepto, Appsilon, IBM, Yalantis, Peerbits, etc
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