Data is the new oil; you keep hearing it again and again in the industry. Everyone is convinced and starts comparing the asset value of data with oil. If you talk to CMO or CDO that’s how they see things. Data needs to be taken care of with utmost care and must have defined procedures and policies in place to ensure no data leakage and data spill.
Recent trends suggest industry leaders are struggling with securing the most valuable resource
Around 45% of firms in the US suffer a data breach
The global average cost of a data breach touched $4.35 million in 2022
It takes around 206 days on average to find out about a data breach
Extensive use of IoT devices and smartphones has been attributed to the growing trend of data breaches
At least 4 incidents of the data breach in 2020 affected more than a billion records
Nearly 82% of data breaches have had a human element
Nearly 75% of firms have said that a data breach has resulted in material damage to their business processes
Source: 2021 DBIR Findings
A report based on an analysis of nearly 79,000 security mishaps with 5,200 confirmed data breaches revealed that stolen credentials were used in more than 60% of security incidents.
A report from the first quarter of 2022 on data breaches has shown that the healthcare industry and health sciences have faced the highest number of breaches, accounting for 26% of 65 data breaches.
I have no doubt data is valuable, but if unrefined it cannot be used. It must be changed into a valuable entity that drives profitable activity; so, data must be broken down and analyzed for value. Large data sets in enterprises are unused and usually kept in cold storage in the hope of future usage. Let’s try to take a different path to understand the data and cost to the enterprise for its management
Data generates more data
Data multiples. It keeps growing, the more you delve into the data, the more data you will end up generating.
Internet users generate about 2.5 quintillion bytes of data each day.
95% of businesses cite the need to manage unstructured data as a problem for their business.
WhatsApp users exchange up to 65 billion messages daily.
The world will produce slightly more than 180 zettabytes of data by 2025.
These are some trends around the amount of data being generated daily. Every enterprise is of the notion, data is valuable irrespective of its form and shape. They have started storing many datasets in hope of usage in the future. This has created a new problem for Enterprises
Creating value out of Data
Enterprises are struggling to prove the value of data, which is lying in cold storage, in the form of logs, raw data, unstructured data and many other forms. Interpreting these large datasets and driving meaningful information is a tedious task and requires massive investment.
Generating value out of such a massive data scale will be a huge transformation program that will require a huge investment and a considerable amount of time.
Dealing or de-linking with Large Data
Enterprises are struggling to find a piece with the large chunks of data, whether they completely de-link or deal with the large data set in day-to-day operations. Both approaches raise the question
If large piles of data need to be de-linked then why has been captured and stored
Does it have any relevance, when in fast-paced digital world customer behavior is unpredictable
How to deal with a large amount of data, it will not require a consistently vast amount of investment
Digital Dust of Data
Every enterprise is struggling with the digital dust of data. In an unprecedented manner, data is being generated across digital platforms, collated, and dusted into cloud storage. There is a massive amount of data duplication across the hybrid cloud.
Some are being used to monitor customer interaction
Some are being used to track customers
Some are being to understand customers
Some are being used for operational efficiency
Data is everywhere. Enterprises are on the hunt to deliver personalized experiences to the customer. Delivering personalized experiences requires capturing customer behaviour, interactions, intention, and movement across digital channels, and to fulfill that enterprises are capturing everything. Nothing left behind. But this data needs to merge with the data from other channels and devices and this is where digital dust comes into play.
We take the programmatic approach and stitch the data based on the use cases, business requirements and needs of the hour. We leave large chunks of data unused and with the passage of time, they turn into digital dust.
Enterprises require an enterprise-wide data strategy to minimize the digital dust, otherwise, it will soon be impossible for an enterprise to make sense of digital dust.
With great data comes great responsibilities
Managing data in a regulated environment is a difficult ask. We discussed earlier how data breach incidents are on the rise across different industry segments. The bigger the datasets, the bigger the problem. The problem is not just about storage or volume of data, but it is around the data types being stored, data tracking practices, level of PII data exposure and much more.
Enterprise needs to ensure the data is not secured when it’s in rest mode but also during flight mode, they have ensured while it’s safe and secure it is also compliant with the fast-changing regulations both at the local and global levels. This does come with a cost, and one minor incident can cost a brand its reputation.
We are in the digital age, in which is evolving, data practices are evolving, so as the regulations, enterprises need to be on their toes to bring more secure, safer cyber practices to safeguard valuable customer data. Enterprises have gone from a VPN lead ecosystem to a proxy setup to Zero Trust architecture and this is a true picture of evolution in terms of data security practices.
Enterprises must introduce cultural changes to ensure data is safe and secure in its last-mile connectivity.
Data and Privacy Regulations
Businesses have been collecting data from their customers without their awareness or consent for a long time. Because the underlying aim of such data collecting is concealed from customers and buried deep inside the terms and conditions, many customers click the “accept to terms and conditions” check box without realizing the implications. They have unknowingly given businesses access to a large amount of personal information.
Because user data has a high market value, businesses aggregate and sell individual personal data on a massive scale. Websites all around the world gather and retain this information in a variety of ways:
Personal information such as a person’s name, gender, IP address, and location
Text messages, emails, mobile applications, and social networking pages are examples of engagement data.
Purchase history and product usage information are examples of behavioral data.
Consumer happiness, purchasing criteria, and product attractiveness are examples of behavioral data measures.
Privacy regulations allow businesses to improve their data handling standards and facilitate cross-border digital transactions. Businesses should expect two big changes as a result of data privacy rules. For starters, customers will have a fundamental expectation of privacy. Second, privacy policy clarity will no longer be optional.
On the other side, from a business viewpoint, the cost of compliance will skyrocket since businesses may be forced to dedicate additional employees and financial resources only to comply with these requirements. Organizations will be obliged to spend to achieve compliance due to significant noncompliance penalties and the possible loss of brand value. Overregulation of policies has another influence on enterprises. Customers are burdened by a never-ending stream of consent forms for every data process.
Monetize Data
With the rising amount of data being streamed and processed daily, several businesses have discovered non-traditional and novel uses for this information, such as data monetization.
Data monetization is the process whereby company-generated data is used to create a measurable economic benefit. Businesses often experience advantages such as increased revenue or reduced expenses because of monetizing their data.
Enterprises are leveraging data and building new revenue streams for their larger business. We have seen in the past companies have come out with Trade Desk and other options to leverage data to their advantage. The industry is leveraging data monetization to
Gain a competitive advantage
Creates new revenue streams
Streamline Operations
Create strategic alignments
Securing what is presumed to be secured
In the modern age of technology, the importance of securing your organization against cybersecurity threats cannot be ignored. Costing as much as €3.3 million on average with 33% of that cost lasting as much as two years after the attack, cyber breaches represent a huge expense for organizations caught unprepared.
The modern era is about the hybrid cloud which means data will be everywhere. No organization can take current security practices for granted, they need to reinvent, reinvest, and adopt more secure standards to allow data security while at rest or in-flight mode
Conclusion
I am sure it’s very clear data is not just data or not just oil. It’s more precious and if not handled properly the enterprise will run for the money. While businesses put money to secure and safeguard the data, they must question themselves
Why they are capturing data
How the data will be leveraged over a period
How they will manage the scale of data
How much investment required not only to store the data but also to drive meaningful interpretation
How they will secure data every second
A Data foundation strategy is instrumental to making the best use of data, after all, data isn’t just an oil
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