Evolution of Legal Sector with Big Data Analytics

Legal Analytics That Makes an Impact

Data is the “new gold” that must be mined optimally to get the best returns. Irrespective of the field, the future of industries lie in how they perceive, process and present the data they have. But was our client- Premonition-a pioneer in the legal industry prepared for the change? Let’s explore.

The Challenges

Our client had crossed the first important milestone of understanding the importance of Big Data analytics in the legal sector. Its realization that it needed expert intervention in the implementation of a legal analytics platform, was the next commendable thing in the line.

The challenges they faced, primarily, were data related. They had an addition of 5GB data every day on their independent instance, which created a lot of pressure on the system and also slowed down the analysis speed.

The second challenge they faced was the scalability of the system during spikes. Volumes of data sent the system under stress, which often led to the system crashing or slowing down. This way a lot of information was lost.

How We Became the Game Changers

Following the principles of Design Thinking, we first built a connection with their challenges, investigating the pain points thoroughly to come up with the best possible solutions. Here’s what we found:

Big data solution for the world's largest litigation database

They had their own instances that were not optimally used, but cost the company thousands.

AWS architecture offering cost-effective solutions

These instances were vulnerable to several security threats

Instance management and the associated pricing was a disarray

Our Solutions

We suggested using the AWS cloud services that not just added scalability to the system, but also helped the company use instances as per their requirements and pay for what they use. For instance, if they required an instance for 2 hours, they would be charged only for those 2 hours, saving them excess cost.

So, to address the high CPU processing or CPU analysis requirement, we recommended the company to use AWS services. This not only reduced their TCO cost but also helped them use the instances optimally.

AWS Code pipeline was used for automatic deployment across hundreds of services. Spot instances were also used to minimize the cost. Parallel server instance was implemented for scrolling. We optimized the server benefit in a cost-effective way.

AWS Architecture Saved the Day

Within months of implementation, there was a visible degree of scalability in the client system, which hampered its performance. The data analysis speed increased by 2X.

A dedicated server would have cost more during the spike season because server capacity had to be added in terms of compute and storage. But our suggestion and implementation helped the company save a lot of money. The tools that we used to build the product included AWS EC2, Lambda, S3, RDS and DynamoDB.

Last Words

The project was close to our heart because of the lesson we learnt during the execution process. Although we had enough expertise and insight into AWS and Legal analytics, the execution helped us hone our skill sets. Gaining a practical knowledge of effectively cutting down on the costs, we learnt to handle data effectively.

We had just started off to implement Design Thinking in our processes and this was the first project which gave us a practical experience of its power. Additionally, the client loved the way we put our agile methodology to use, involving them at every stage from ideation to execution and testing and fine- tuning the product at every process cycle. This avoided errors during the launch of the product.

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