We regularly work with substantial volumes of real-time and historical data, with individual tables comprising hundreds of billions of records.

Our in-house massively parallel processing capabilities and a team of programming specialists ensure that we can conduct large-scale data analytics efficiently and effectively. Our specialized expertise and secure computing facilities allow us to maintain, update, and manage the public and private data used to support expert consulting and testimony.

These resources allow us to ensure ongoing data integrity and navigate the evolving data needs specific to the numerous stages over the potentially long-range horizon of litigation, regulatory, and investigation matters. Our cutting-edge information-retrieval and management tools minimize business disruption and create efficiencies for our clients.

Client Data Production

Clients frequently rely on us to compile large datasets from disparate sources and incompatible formats. We also manage outside vendors for data entry, extraction, and reconciliation to minimize the cost of construction.

We help counsel manage the discovery and data production process and work with clients to thoughtfully and efficiently extract information in anticipation of the analytical needs of subsequent phases of work as well as in response to direct requests from regulators or litigants.

  • Cigna’s Acquisition of Express Scripts
    Supported economic analysis and data production.
  • Addressed issues involving large healthcare claims data analytics, patient record linkage, and de-identification.
  • Analyzed overdraft fee practices in consumer financial services class actions, including individual account-level transaction data for millions of customer accounts.
  • Collected and processed millions of data records for day-ahead, day-of, and real-time California energy markets. Our work entailed analyzing detailed and complex bid, price, and settlement data for all participants in each market.
  • Analyzed large databases that contained transaction-by-transaction and quote-by-quote data on all equity trades and quotes in U.S. equity markets for five years. Analyzed equity audit trails from National Association of Securities Dealers files containing information on every quote and transaction by individual market makers.
  • Anderson News LLC et al. v. American Media Inc. et al. Analyzed terabytes of delivery and sales data for more than 120,000 individual retail outlets and thousands of magazine titles.
Secure Analytics Infrastructure

The rapid growth in the volume of data collected and generated by companies across nearly every industry has created new challenges and opportunities for analyzing data at scale. Cornerstone Research has heavily invested in secure, on-premises analytics infrastructure, including sophisticated, high-performance and high-throughput hardware and software. We are also experienced in leveraging cloud computing capabilities for surge storage or compute capacity.

  • Deployed server infrastructure interfacing with various cryptocurrency networks to collect and analyze hundreds of gigabytes of real-time and historical ledger data. Ingested and analyzed a table with 300 billion rows of order book data.
  • Gathered public data using cloud infrastructure by leveraging our experience with Amazon Web Services and Microsoft Azure.
  • Completed regular SOC 2 Type I and Type II audits related to data security, availability, processing integrity, confidentiality, and privacy.

Featured Matter

Cornerstone Research’s Data Science Center assisted in investigating plaintiffs’ claims in an alleged market manipulation class action. With over 200 TB of high-frequency trading data provided, the Data Science Center determined the best protocol to access these large and complex datasets. The team also helped identify the relevant data subsets that would be used in the analyses.

To conduct these analyses, it was critical to understand the characteristics of these databases, how the different tables were connected to each other, and the evolution of the data structure over time. The Data Science Center assisted in identifying and collecting the relevant information, which allowed the team to understand these complex databases.

Under the direction of the testifying expert, the team helped develop complex code that relied on the understanding of these large databases in order to conduct multiple analyses.