SofTeCode Blogs

One Place for all Tech News and Support

5 reason’s to learn Data Science and Cyber Security

4 min read
data science and cloud computing network

image by freepik


Consider Data Science & Cyber Security as two powerful engines empowering the digital economy of today and tomorrow. The premise of digital economics relies on the inter-relationship between data, business value, and managerial deciding . With increased adoption of digitization and digital transformation, we’ll consume more data than ever before. Rightly, it’s considered the new oil of recent times. As Alphabet’s Eric Schmidt states, every 48 hours, we generate more data than humanity produced since the dawn of civilization until 15 years ago. the large question is, how are we getting to make meaning of all that? Data Science isn’t just a buzzword. Today, no company can prosper without the insight of knowledge. That’s why, if you compare Fortune 500 companies of this year with the 10-year-old list, you’ll realize only the info-driven companies have performed consistently and became the new winners of the digital economy.

And, as we move the planet of brick and mortar into the digital world along the new and emerging models of companies , the danger of security also crops up exponentially. Yes, information technology has bridged the gap, between nations, companies, buyers, and sellers and markets, but it also means we are increasingly leaving our digital footprints along the way. and a few entities are storing that data. So, regardless of how secure an organization’s or country’s data may look unbeatable, it’s going to actually disintegrate one fine morning and expose personal, financial and sensitive data call at the open.

Five reasons why it’s important for the digital economy to leverage data science and cybersecurity for its own good.

Data Science

  • Data Storage and Retrieval: Story of knowledge science originates from storing knowledge. we’ve stored them in our heads, earthen slates, paper then on the pc. Today’s onslaught of massive data anyway has got to be collected and extracted. With the abundance of IoT devices endlessly generating and transmitting data, businesses need to store and retrieve a high-volume, high-velocity, and high-variety unstructured data.
  • Data Cleansing: you’ve got tons of knowledge at your disposal but an honest percentage of them are useless, outdated, incorrect or difficult to format. The challenge here is to make a pleasant , easy to use formatting and conforming to internal quality rules. Many believe data sparseness and formatting inconsistencies are the most important challenges. When more data pours in, the spreadsheet turns into a knowledge base and turns into a data warehouse. Without proper data science interventions, companies can’t ensure clean data sets.
  • Data Analysis: Data analysis is vital to know problems faced by an organization, tons of your time there might not be any evident problem but by predicting customer trends and behaviors, analyzing, interpreting and delivering data meaningfully, businesses can enhance productivity and drive effective decision-making.
  • Modeling, statistics: Application of statistical analysis to a dataset holds immense value to any industry be it manufacturing, retail, or fintech. rather than sifting through data interprets relationships between variables, predicts future data sets, and helps you see patterns. With the assistance of machine learning and AI companies are leveraging statistical models to create representation of knowledge .
  • Engineering, prototyping: Clean data and an honest model is simply the start. It means developing some kind of data tools or products in order that cross-team collaboration can happen and non-data scientists, internal employees like business analysts, etc. can use them internally for visualization, dashboard or applications

Cyber Security

  • Protection against malware, ransomware, phishing and social engineering: The cybersecurity landscape is consistently evolving. Attackers often use a mixture of ransomware or social engineering for instance – to maximize the impact. regardless of what proportion we heighten our technology around security and make our human folks aware, human elements will remain susceptible to innovative attacks. Modern digital businesses got to specialize in strong firewalls, VPNs and advanced malware, ransomware, and phishing protection alongside supporting email and endpoint security.
  • Protection for data and networks: In its simple form it’s a group of rules and configurations designed to guard the integrity, confidentiality, and accessibility of computer networks and data using both software and hardware technologies. thanks to digitization, our world has changed. All organizations, no matter size, and scale, connected customers and employees digitally are exposed to the ever-growing landscape of cyber threats and must protect its network.
  • Prevention of unauthorized users: A security breach or data breach within the sort of unauthorized access happens when an attacker successfully gains unauthorized access to an enterprise system namely, data, networks, endpoints, applications or devices. This happens through three stages, the attacker successfully researches the vulnerabilities, evades network defense then exfiltrates with data. Businesses can protect such attacks through strong password policy, Two Factor Authentication (2FA) and Multifactor Authentication, Physical Security Practices, Monitoring User Activity and Endpoint Security.
  • Improves recovery time after a breach: Experts estimate that ransomware attacks are up over 600 percent, says a Microsoft report. Planning for data breaches and having a strategic approach through disaster recovery should be a baseline activity. an honest and current offline backup is that the initiative. Offline backups are out of reach of ransomware and cyber thieves. Having documented centralized logs right before the incident helps forensic to urge to the basis cause.
  • Improved confidence within the product for both developers and customers: Over the years, organizations became more mature, aware, and have placed systems in situ as far as business risk assessment cares. Despite issues, when leadership expresses confidence in their abilities to guard their organizations from cyber-attacks, it goes well with employees, developers, and customers also.



Healthcare Organization Big Data challenge – Cloudera

Learn Cloud skills with Google Cloud training

How useful was this post?

Click on a star to rate it!

Average rating 0 / 5. Vote count: 0

No votes so far! Be the first to rate this post.

1 thought on “5 reason’s to learn Data Science and Cyber Security

Give your views

This site uses Akismet to reduce spam. Learn how your comment data is processed.