Are You Prepared to Conquer Data Challenges in 2020?

Widespread adoption of cloud hosting has made processing huge amounts of data worldwide not only possible but, the norm. While organizations continue to move operations to the cloud posthaste, an estimated 94% of workloads will be processed there in 2021. A Sysgroup survey attributes the main driving factor behind this exodus to the capability of providing data from anywhere.

Big data certainly presents difficulties from complexity to security in the world of eDiscovery. These difficulties also vary with the types of data involved. Here, we take a look at the challenges associated with discoverable data and its sources.

Challenges associated with data in 2020

Complexity

Data complexity is contingent upon the degree to which it is structured. Structured data is very easy to work with, as it is usually highly-organized and easily-searchable. On the other hand, unstructured data is not systematically organized aside from its own internal structure. This lack of systematic organization complicates traditional methods of search and discovery.

However, more and more data come from unstructured sources. Figures from the IDC predict that as much as 80% of data will be unstructured by 2025. These sources may be either human-generated or machine-generated including, but not limited to, chat logs, sensor data, and business applications. Figuring out the most optimal and efficient ways of managing and discovering this data will be imperative for organizations to remain competitive.

Privacy and Security

The reality of the rise of the Internet of Things is that correctly and safely handling sensitive information has become increasingly tedious. Data privacy has moved to the forefront of software users’ minds, as individuals become more cautious of how their data is shared. This awareness has pushed data privacy and security to become critical components of data management.

Regulatory measures are usually slow to catch up with developments in technology, however, it is still necessary to be on top of the latest rules. GDPR and CCPA violations can result in heavy penalties with regards to the mishandling and sharing of Personally Identifiable Information and Personal Health Information.

Additionally, hacking and data breaches have become an omnipresent threat. Security breaches have grave consequences, proven by high-profile data leaks. After a hacker gained access to Capital One’s highly-sensitive customer information and credit applications early this year, customer confidence has dropped massively. The bank additionally expects to see reduced revenues over the next several years as well as a $15 drop in its stock valuation.

Several mistakes organizations make with handling sensitive data are:

  • Lack of attention to where cloud applications are processing and storing data
  • Collection of unnecessary data
  • Failing to meet security standards and implement processing agreements
  • Failing to enact measures ensuring the possibility of data deletion once someone finishes using service

Volume

It is estimated that in 2025, 463 exabytes of data will be produced each day. One exabyte is equal to 1,000,000,000,000,000,000 bytes. When handling this much data, it is extremely difficult to determine what’s relevant. With enormous amounts of data coming in from those connected to the Internet of Things, organizations are going to be confronted with challenges dealing with cost and efficiencies.

When dealing with massive volumes of data for litigation; collection, processing, and review may be excruciatingly slow. With a litigation hold, it can also be difficult to know what’s needed and what can be ignored. Additionally, in some cases, documents must also be reviewed in person. Can you imagine manually combing through a database, byte by byte, in to discover relevant documents? Without proper controls, timeliness is thrown out the window and the discovery process becomes a nightmare.

What This Means For You

Going forward, managing data is going to become more complicated and require more effort. Complexity, privacy, security, and volume all pose challenges that organizations must learn to overcome in order to remain competitive and efficient.