Data has always been king, but the pandemic has expedited digital transformation. As a result, more companies are using digital formats than ever before, but many lack the tools to adequately protect that data and are vulnerable to a cyberattack. Additionally, these companies are collecting more data than they even know what to do with and need to consider using more powerful data processing platforms to help expedite the process. 

So much data is being produced on a daily basis that governments from around the globe recently met at the General Conference on Weights and Measures to vote to introduce new prefixes to the International System of Units. By the end of this decade, the world will generate a yottabyte every year — or 1024 bytes — a number that is hard to even fathom. With the rise in data comes new challenges, such as how to quickly navigate to relevant data and how to keep all of that data safe from cybercriminal activity which is set to cost the world $10.5 trillion by 2025.

From Consumer Data to Company Data

Consumer data has always been used to target interested demographics while company data is being used in new ways to improve operational efficiency and safety thanks to the expansion of wearable sensor technology. Companies looking to monetize this data will need to take reasonable precautions to protect this data and prioritize consumer privacy. Not only will these precautions reduce company liability, but they will save on costs by preventing unnecessary legal actions and lost business resulting from irreparable brand damage in the event of a data breach.

Types of Data Being Collected

Before a data analyst begins data collection, researchers must first identify the data types, the source of that data, and the methods they intend to use to extract that data. The number of data sources has increased dramatically over recent years as companies are able to track every transaction and follow up with those customer interactions with surveys to get their feedback. 

Companies no longer just track transactions, but they also track how consumers interact and how long they engage with a business’s website, mobile application, email campaign, text messages, social media, and any other paid advertisements. Conducting interviews, strategic observations, focus groups, and using secret shoppers or social media to get additional feedback data for consumer-facing interactions can be invaluable sources of data as well. 

  • First-Party Data – Data that is collected directly from users through the organization.
  • Second-Party Data – Data that is shared by another organization about its customers that has applications for other businesses in the industry.
  • Third-Party Data – Any other collection of data that is rented or sold by organizations that do not have any personal connections to your company or its users.
  • Qualitative Data – Data can be broken down into descriptive terms such as color, size, quality, and appearance. 
  • Quantitative Data – This type of data typically involves numeric assessments that utilize statistics, polling numbers, and other percentages.

Companies also look to improve their back-of-house operations by monitoring production data for areas of improvement. This has become exceptionally more complex as more machinery is embedded with sensor tracking technology and artificial intelligence. Whether performing a self-audit or comparing their numbers to their competition, companies are likely tracking their financial statements, sales reports, distributor feedback, customer personal information, government tax records, shipping status, and socials. The sources for data continue to grow in complexity and will make analyzing content an even more nebulous process than it already is.

Why Data Consolidation Applications Are Needed

The Data Avalanche and What it Means for Legal Ops Professionals1. Meet the Demands of Growing Data Volumes

Corporate legal teams have always been looking for ways to reduce the data they really need to collect, store, and process so they can focus their collection efforts on the data that best correlates to a designated business goal. However, attempting to be more selective with data collection is an idealistic solution that may not be feasible for much longer given the sheer volume of data being produced. 

Simple data reduction used to make it easier to secure and verify data accuracy, but companies need to adjust their plans to include data consolidation tools in order to address the growing volume that needs to be tracked. Using modern-cloud based eDiscovery solutions such as Casepoint can help companies navigate massive stores of data far more quickly than human operators alone and can facilitate more timely and thorough data analysis.

2. Offset Labor Shortage and Burnout with Efficient Programs

Since the data cannot be reduced and the field of data science is experiencing labor scarcity, the only solution that remains is to work smarter — not harder. In other words, automating processes with applications that are more efficient will reduce the data workload for the 97% of data engineers reporting burnout on the job. The best way to future-proof data collection strategies in an increasingly data-rich society that lacks the labor resources to meet such high demand is to utilize applications or platforms designed to intelligently organize and consolidate data for greater visibility and efficiency. 

3. Avoid Regulatory Fines, Legal Fees, and Negative Brand Impact

With the introduction of legislation like the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), it has become more of an imperative for companies to be compliant with data privacy laws. It is no longer simply a moral imperative to practice data ethics since there are now hefty fines that can be imposed for noncompliance for businesses operating in the EU and California where the less severe infringements can still result in €10 million fines. For businesses that operate outside of California and the EU, they still need to make good-faith efforts to protect the data privacy of their users to avoid expensive lawsuits

Preserve Company Integrity and Maintain Efficiency with Data Integration

Using eDiscovery solutions with better data consolidation capabilities and more advanced security measures can help corporate legal teams avoid costly breaches or other fines altogether — including negative impacts to the company brand in the event of a breach. To avoid data misuse and preserve company integrity, corporate legal teams need to establish data governance programs that utilize apps that encrypt data to facilitate safe data collection and storage practices. Using eDiscovery platforms with robust data processing to unify the data that is collected will ultimately reduce a company’s liability while increasing its efficiency and data visibility for improved predictive analytics.

Download “The Data Avalanche” whitepaper to get access to seven readiness steps that you can take today to overcome your most complex eDiscovery data challenges.

The Data Avalanche

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