Big data is valuable, but without human intervention, it may sit untouched, which can limit an organization’s opportunities to make informed decisions. Big data analytics consulting can help business owners develop strategies for interpreting and processing data, and help uncover patterns, correlations, and trends that humanize the data — which allows organizations an opportunity to gain a competitive edge.
Data-driven storytelling is the process of translating data findings into a story that draws an audience in. Emotions influence what we buy, and by writing in a way that appeals to a consumers’ emotions — and using valuable data — you create branded content that can invoke a response or decision.
Data analysis and data-driven storytelling are complementary processes and skill sets that business owners and other executives should improve upon — this is because:
Consumers want evidence behind claims, but most individuals will not automatically understand analytics. Organizations need to provide contextual information to fully drive data points.
Customers provide relevant information, and organizations can use this information to improve and build upon current processes. It can help determine value, manage risk, and improve services/offerings.
By humanizing data, you gain insight into why this is important for specific demographics. Organizations can relay this information to consumers and encourage action as a result.
When done effectively, data-driven storytelling can create a solidified brand narrative by leveraging information found within your data. This is a powerful way to show – not just tell – your story. In doing so, your campaign efforts become more credible, effective, insightful, and engaging to your customer.
Big data analytics are beneficial within a number of industries, and by using proper data hygiene you can improve your business strategy as a whole. Data is generally based on humans, so at some point, humans should be involved in handling the data. Automation in the workplace is extremely useful, but not all processes can (or should be) fully automated.
Humanized data doesn’t need to be overly complex, but by following several simple strategies, you can greatly improve your organization’s success.
Data is vital to enhancing business growth, but unless you tie data to customer outcomes, it is essentially useless. Explain why the information is important for customers specifically. If you want to use this data viably (i.e., minimum viable data for decision making), you need to take the time to fully understand what the numbers are, what they are telling you, and communicate these outcomes to your stakeholders via text or visuals.
Not everyone can look at a set of numbers, or industry language, and understand what this means. Translate your big data points into easy-to-understand language. Utilizing numbers can be beneficial, but you want to relay this information in an informative, straightforward manner.
Being direct is important for both your organization and your customers to understand the meaning of the data. You don’t always need a preamble — simply get straight to the point. If your team members understand the data, they can better represent that information when presenting it to consumers.
Individuals learn differently, and using visuals can help benefit specific types of readers. Pictures, graphs, and diagrams can all help reinforce data points. Use the following tips to create effective visualization of your data:
Carefully choose the right charts and graphs for visualizing the data
Avoid misrepresenting your data
Present the data in multiple ways
Apply text when necessary
Use size to emphasize important information
Utilize color cues
Keep things simple
Visualizing data discovered by analytics or analytics services can have a variety of benefits for your business. Some of the benefits behind creating data visuals may include:
Using visuals can help readers comprehend large amounts of information in a simple manner.
When you look at a bunch of numbers, you may not understand relationships without visually representing them. This can help organizations recognize patterns at scale and strategize accordingly.
If the data displays a response other than what you had intended, you can change your efforts/processes accordingly.
When you have real-time data monitoring, you gain immediate insight into the various processes within your organization. This can provide information surrounding employee performance, the buyer’s journeys, and even things like energy inefficiency.
The best way to take advantage of data humanization is to invest in a firm that specializes in data-driven digital transformations. These firms help analyze organizational data and craft innovative strategies that achieve the desired outcomes. Utilizing this type of service can ensure fast, consistent analysis and data processing so that you can focus your efforts elsewhere.
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
Application Modernization at Speed and Scale Enterprises are pursuing greater application scalability, cost efficiency, and standardization with containerization and virtualization platforms. So, what’s the difference? Containers are a type of virtualization technology that allows users to run multiple operating systems inside a single instance of an OS. They are lightweight and portable, making them ideal for running applications across different platforms.Explore
Container Orchestration or Compute Service? Amazon Web Services (AWS) offers a range of cloud computing services to meet enterprise needs. Included in its service offering is the elastic compute service (ECS) and elastic compute cloud (EC2). Choosing between these two services can be difficult, as one focuses on virtualization while the other manages containerization. In the following article, we will explore the differences between Amazon ECS and EC2 to help you better understand which service is right for your use case.Explore
What is Application Modernization? Application modernization is the process of converting, rewriting, or porting legacy software packages to operate more efficiently with a modern infrastructure. This can involve migrating to the cloud, creating apps with a serverless architecture, containerizing services, or overhauling data pipelines using a modern DevOps model.Explore