Big Data Use Cases
Make Voracity Work for Your Business
Big data is creating new opportunities for data-driven enterprises, and turning more and more companies into competitive digital businesses. The IRI Voracity data management platform consolidates big data discovery, integration, migration, governance, and analytics in an affordable, agile Eclipse framework that IT and business users, data scientists, and data security teams can share.
Take a look at just some of the opportunities in big data that Voracity can help you leverage!
Expose Insurance Fraud
Tracking transactions in one account, lender, or provider is easy. But across thousands or millions or transactions, the data can become too large and interwoven to handle, which creates the opportunity for risk. Use Voracity to sort and filter data for values out of range. Join values against known problems or people to identify suspicious transactions, and flag events that “fit the profile” of fraud. Tie your own algorithms to Voracity jobs, and use the visualizations you prefer in its GUI. Combining data munging and mining helps find and disable accounts faster so you can prevent losses and enforce laws more effectively.
Optimize Loan Performance
Commercial lenders can leverage big sources of external and internal data to avoid risky loans. In addition to the borrower’s credit history, they examine legal regulations and market forces, climate, social data, industry repayment statistics, and the financial health of similar businesses in the region. With this information, repayment rates can be adjusted to match the weight of these factors before they ever become an issue. Use CoSort or Hadoop engines in Voracity to filter, sort, join, aggregate, mask, and hand-off these data points to tools like Tableau so visualizations can materialize at least 8x faster.
Assess Credit Risk
Credit risk scoring was one of the first applications of big data in the financial services industry. It started decades before Hadoop and advanced analytics in large credit bureaus like Equifax using CoSort and big servers to sort and integrate millions of historical data points. Companies like CoreLogic use similar techniques, and can now leverage CoSort and Hadoop engines in Voracity to blend traditional credit data with sources like utility bill and rental payments. This can improve score accuracy, and facilitate bank and non-bank lending, marketing, and collection for previously unscorable, or higher-risk, borrowers.
Telecommunication and cable companies have a unique position in the world of big data in that their customers provide valuable, granular information every time they use a service. Onboarding and Call Detail Records (CDRs) provide data ranging from demographic and geographic to device usage and content preference, as well as predictive data from call, SMS, web, and app history. Use Voracity to process CDRs and clickstream data not only for billing and analytics, but for legal investigations and infonomics; i.e., selling what’s permissible to “affiliates” who can use preference data relevant to their businesses.
Big data means data extracted from traditional and current sources of consumer preferences to trend the demanded and popular content. Use Voracity to extract string and pattern-matching values from social data from Hubspot and Marketo, and mash it up with internal transaction and public demographic data to identify viewing, surfing, and spending habits, establish ratings and rankings, understand opinions, and discover other factors that identify target audiences and predict the kinds of content your customers or prospects will want … before they even know they want it.
Patient health should be evaluated as a spectrum, not just through discrete data points from hospital or office visits. Blood pressure and glucose checks, pacemaker-to-EMR feeds, etc., produce data streams for more holistic patient observation. IoT healthcare data can flow through slowly changing dimension or changed data capture reports in Voracity to compare new data baseline and diagnostic values that can spot abnormalities. The same workflows can also produce visualizations, and email patients and physicians with reports before a crisis occurs … potentially improving treatment outcomes, and saving lives.
Data on human cell-lines and the genetic and environmental factors that affect them produce phenotype data, which in itself is a great source of knowledge. Drug studies conducted on known human and mouse phenotypes reveal changes in gene and protein expression in their cell-lines. Voracity can help you rapidly integrate genetic data into single-node-type networks, gene-set libraries, and bi-partite graphs so you can reveal more relationships between genes, drugs and phenotypes. This kind of digital science application to biodata can help produce more individualized, and effective, therapies.
See the whole Patient
Much like the unified view of the customer, the unified view of the patient can be a golden electronic medical record (EMR) containing their medical, pharmacological, and family history, plus demographic, diagnostic, treatment, and prognosis data. Voracity can join dimensional data in different files or tables to a patient, remove duplicates and reconcile conflicts, and de-identify protected health information (PHI). These data integration, cleansing, unification (MDM), and masking features help you create HIPAA-compliant views of patients to improve medical care and support research.