“Big Data Analytics” is the new buzz phrase when it comes to finding knowledge tucked away within corporate databases. While “Big Data” provides opportunities for corporations it also presents new challengeson what to collect, how to collect it and how to analyze all that you have. Within the context of corporate disputes we can help in winning the battle of the experts when dealing with massive data sets. By performing analysis across all of your data our data analytics methodologies allow for the elimination of estimates, extrapolation or sampling and will provide complete results and totals through the creation of data warehouses and the utilization of data mining.
Primarily used in the dispute context towards class action lawsuits, bankruptcies and settlements, claims management deals with the identification, management and disbursement of funds to numerous individuals.
Consists of analyzing transactions in a litigation setting to aid in assessing damages owed to or by the parties.
Analyzing data from corporate financial systems to identify anomalies that may be the result of improper transactions or fraud.
Analysis of data within the context of an ongoing investigation. Data is typically from accounting systems, server log files, PC log files, and various other sources aggregated for analysis to a centralized data store.
The licensing of technology, works of art, processes, copyrights and other transfers. Transactions and methodologies are reviewed to determine if royalty payments are compliant with the terms of the contract.
Using corporate data to analyze trends or patterns amongst clients, sales, products, regions, employees, inventory, Internet traffic, etc.
Our multi-discipline data analytics process follows closely a system implementation and develop process combining methodologies for data warehousing, custom application development, information analysis and litigation support. It is not just about being database experts. Combing these disciplines in essential to once again winning the war of the experts and understanding how to present your results through:
Complex data analytics is centered around the analysis of transactions. One transaction might be the purchase of an item, a phone call, an Internet download, a payment or a sale. What makes this type of analysis complex is that the analysis is performed across millions, hundreds of millions and even tens of billions of individual transactions. The data may be analyzed across time, by business entity, types, amounts, accounts, locations, products, users or any other information that is related to the transaction.
Using powerful databases and systems configured for massive analysis, data from multiple sources is aggregated to a centralized location. Once there the data is transformed to a structure that will facilitate the analysis. Data within transactional systems such as your core business applications is structured in a manner that facilitates the completion of a transaction. The optimal structure for the completion of a transaction is not the same if the needs are to analyze the data. Such a system where data from multiple sources is integrated to a centralized location and the data is transformed to fit an optimal analysis structure is often referred to as a data warehouse.
