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 decision making. With increased adoption of digitisation and digital transformation, we will consume more data than ever before. Rightly, it’s considered the new oil of modern times. As Alphabet’s Eric Schmidt states, in every 48 hours, we generate more data than humanity produced since the dawn of civilization until 15 years ago. The big question is, how are we going to make a meaning of all that? Data Science is not just a buzzword. Today, no company can prosper without the insight of data. That’s why, if you compare Fortune 500 companies of this year with the 10-year-old list, you will realize only the data driven companies have performed consistently and have become the new winners of the digital economy.
And, as we move the world of brick and mortar into the digital world along the new and emerging models of businesses, the risk 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 some entities are storing that data. So, no matter how secured an organisation’s or country’s data may look unbeatable, it may actually fall apart one fine morning and expose personal, financial and sensitive data out in the open.
Five reasons why it’s important for the digital economy to leverage data science and cyber security for its own good.
- Data Storage and Retrieval: Story of data science originates from storing of data. We have stored them in our heads, earthen slates, paper and then on the computer. Today’s onslaught of big data anyway has to be collected and extracted. With the abundance of IoT devices endlessly generating and transmitting data, businesses have to store and retrieve a high-volume, high-velocity, and high-variety unstructured data.
- Data Cleansing: You have a lot of data at your disposal but a good percentage of them are useless, outdated, incorrect or difficult to format. The challenge here is to create a nice, easy to use formatting and conforming to internal quality rules. Many believe data sparseness and formatting inconsistencies are the biggest challenges. When more data pours in, the spreadsheet turns into a database and turns into a data warehouse. Without proper data science interventions, companies can’t ensure clean data sets.
- Data Analysis: Data analysis is important to understand problems faced by an organisation, a lot of time there may not be any evident problem but by predicting customer trends and behaviours, analysing, interpreting and delivering data meaningfully, businesses can enhance productivity and drive effective decision-making.
- Modelling, statistics: Application of statistical analysis to a dataset holds immense value to any industry be it manufacturing, retail or fintech. Instead of sifting through raw data interprets relationships between variables, predicts future data sets and helps you see patterns. With the help of machine learning and artificial intelligence companies are leveraging statistical models to build representation of data.
- Engineering, prototyping: Clean data and a good model is just the beginning. It means developing some sort of data tools or products so that cross-team collaboration can take place and non-data scientists, internal employees like business analysts etc. can use them internally for visualisation, dashboard or applications
- Protection against malware, ransomware, phishing and social engineering: The cyber security landscape is constantly evolving. Attackers often use a combination of ransomware or social engineering for example – to maximise the impact. No matter how much we heighten our technology around security and make our human folks aware, human elements will remain vulnerable to innovative attacks. Modern digital businesses need to focus on strong firewalls, VPNs and advanced malware, ransomware and phishing protection along with supporting email and endpoint security.
- Protection for data and networks: In its simple form it is a set of rules and configurations designed to protect the integrity, confidentiality and accessibility of computer networks and data using both software and hardware technologies. Due to digitisation, our world has changed. All organisations, regardless of 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 in the form of unauthorised access happens when an attacker successfully gains unauthorised 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 defence and 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. A good and current offline backup is the first step. Offline backups are out of reach of ransomware and cyber thieves. Having documented centralised logs right before the incident helps forensic to get to the root cause.
- Improved confidence in the product for both developers and customers: Over the years, organisations have become more mature, aware and have placed systems in place as far as business risk assessment is concerned. Despite issues, when leadership expresses confidence in their abilities to protect their organisations from cyber-attacks, it goes well with employees, developers and customers as well.