Data mastery. Likely a skill few practitioners gave a second thought to years ago – now stands as one of the biggest challenges for tomorrow’s lawyers and discovery professionals. More and more, data and how it is utilized to build cases, faster and more effectively than the opposition will drive the legal landscape. The growth and potential of data – and data analytics – and how humans adapt to all of it is transforming the legal industry.
Technology Got Us into This Mess
One of the biggest challenges – and I would argue, potential opportunities – that lawyers and discovery professionals face today is Big Data. You’ve certainly heard of Big Data and may have heard several of the stats associated with data growth. In case you haven’t, here are three stats to consider:
- The amount of data in the world doubles every two years.
- 95% of businesses cite the need to manage unstructured data as a problem for their business.
- By 2025, the amount of data in the world will have grown over 1,800 times in 20 years – from 0.1 zettabytes in 2005 to around 181 zettabytes in 2025, which is 181 trillion gigabytes.
A big reason we’re in the “mess” we’re in today is the role technology has played in creating a seemingly impossible amount of data for organizations to manage. There are so many apps and devices creating so much data, companies are becoming overwhelmed by it all.
Reliance on collaboration apps like Slack, Teams and Zoom and even other collaboration apps like Zendesk, Trello, Basecamp, Asana (and more) have skyrocketed, as has the usage of other cloud-based enterprise solutions. Mobile devices are becoming the primary device being used for internet access and even email. Even Internet of Things (IoT) devices must be considered today, and generative AI needs large volumes of data to train the algorithms that fuel its accuracy.
How does that relate to tomorrow’s lawyers and tomorrow’s “discoverers”? With twice as much data to consider in discovery every two years, they must adapt to handle it all – budgets won’t double every two years.
Technology Will Have to Get Us Out of This Mess
While information governance policies and best practices are important to helping address the Big Data challenge of today and tomorrow, policies and best practices alone won’t cut it. Just as technology got us into this “mess”, technology will also have to get us out of this “mess”. Here are three stats to consider how companies are approaching technology’s role in addressing the Big Data challenge:
- The demand for composite data analytics professionals will grow by 31% by 2030.
- 96% of companies plan to hire job seekers with big data skills.
- Over 97% of organizations are investing in big data and AI technology.
Tomorrow’s Discoverers: Data Oriented Jobs
With that in mind, let’s take a closer look at data-oriented jobs for and how they will conduct those jobs as discovery challenges – and technology to address those challenges – continues to evolve.
Traditional manual investigation processes can be time-consuming and resource intensive. Tomorrow’s investigators will need to take advantage of Big Data technologies, which index large volumes of data within the enterprise, to conduct investigations faster and more efficiently. Automation of previous manual tasks such as data collection, processing, and analysis will be needed to reduce the time spent on gathering data, enabling investigators to focus on interpreting the results, identifying relevant trends, and conducting targeted inquiries. This increased efficiency will help generate critical insights that expedite investigations and minimize disruption to business operations – in 72 hours or less.
Enterprise Forensic Examiner
In the era of Big Data and enterprise solutions, forensic examinations have undergone significant changes. Traditional forensic tools may not be capable of effectively analyzing and extracting evidence from large datasets. Therefore, new tools and technologies have emerged, such as distributed computing, parallel processing, and data visualization, to assist in managing and analyzing Big Data during forensic examinations. To address today’s Big Data challenges, forensic examiners have been forced to adapt, by embracing these new tools and techniques to quickly gain targeted insights within Big Data repositories. To obtain desired outcomes, the enterprise forensic examiner will not only need to be able to master increasingly complex examination processes, but they will also need to be able to explain those processes in “layman’s terms” during testimony at hearings and court proceedings.
Data scientists are likely to develop deeper domain expertise in discovery and related disciplines. By combining their knowledge of data analysis and machine learning with a comprehensive understanding of the industry’s challenges and requirements, data scientists will be able to provide more targeted and impactful insights than ever. They will also play a vital role in ensuring responsible AI practices, proactively considering fairness, transparency, accountability, and privacy when developing and deploying AI models. And they will likely increasingly integrate specialized capabilities to address discovery challenges, including natural language processing (NLP), computer vision, deep learning, reinforcement learning, or domain-specific knowledge. The sky is the limit in terms of what data scientists will be able to accomplish to automate processes and quickly gain critical insights into increasingly huge datasets.
Technology’s ability to generate huge volumes of data has considerably outpaced our ability to effectively manage that data. Tomorrow’s data-oriented discoverers will have to reverse that trend, utilizing technology to master that data and support the needs of lawyers as they tackle ever-more complex challenges in a fiercely competitive landscape.
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