Cyber Security with Graph-based Approach: How and Why

As the world of business and technology is increasing and merging, the amount of data is also immense. Dealing with a vast amount of data can be frustrating if you do not understand how to deduce or analyze it. Data literacy in C-suite is the ability to read, understand, analyze, and communicate with data. Data literacy and analysis make it easier to share knowledge, make relevant decisions, and communicate effortlessly. Market intelligence is crucial to troubleshooting problems and increasing revenue. 

Out of the research conducted on 7300 business companies, only around 25% admit that they are data literate and can handle the operations well. 17% of company employees still struggle to convince their team about the data science program and its importance in today’s world. Apart from the difficulties faced in some businesses, 94% of the crowd believe that data science and technology make their job easier and faster. If provided with proper opportunities, many employees agree to enhance their data skills in the companies. 


With the increasing data, we also have to manage them effectively. Company leaders and employees must be data literate to understand the technical communication and rectify the errors in the business. Having strong data skills helps to combat technical errors and plan a strategic solution for the business model. 


Not understanding the data can be the biggest barrier to the evolution of business. Only around 28% of C-suite executives believe that employees are comfortable with data stats. In any business or company, it is crucial to have leaders literate in data analysis to guide the rest of the team. Being tech data-savvy provides more credibility at the workplace. As a leader, one should motivate their team to take up the data literacy program to bridge the skill gaps. Achieving data literacy is:

  • the keystone to making data-driven conclusions
  • prerequisite to analyze and interact with the data meaningfully
  • the basis for effective data management 
  • assists companies make moral AI and data analytical decisions
  • helps build and improve the data literacy rate within an organization or company. 


With the rapidly advancing technology, there is a lot of hype and curiosity increasing around Data Science, Artificial Intelligence, and Machine Learning. The team members need to be in the loop of these fields and relate them to their business models. Data literate individuals can identify opportunities and gain benefits from the available data and technology. C-suite leaders understand the importance and challenges of the data science cycle. It helps them work better towards their goals of analytics and ensure positive outcomes in the business. The main steps in the data science cycle include: 

  • Problem identification
  • Gathering relevant data of the problem
  • Identify crucial variables
  • Create or recreate and validate the business model
  • Install the model into the business process
  • Monitor results and keep updating them with newer and enhanced technology.

The data science cycle can be daunting. It can be achieved only with a clear focus and data literacy. Critically analyzing the problems and delivering appropriate solutions is no laymans’ work. Having a business model, advanced technology, appropriate data integration, is of utmost importance for a successful service.

Data literacy helps C-suite members make well-informed decisions regarding a product or service. They can do a quick SWOT (Strength, Weakness, Opportunities, and Threat) Analysis and agree on a common base for the betterment of the business or the company. Data literacy also ensures ethical use of the data and prevents legal entanglements. Such individuals are well aware of the consumer market and understand the valuable, operational data. Choosing accurate metrics and variables is important to determine the business failures and successes. Data science literacy instills confidence, willingness, understanding, and critical thinking in terms of the business and consumer point of view.