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Unlock the Power of Standardization, Normalization, and Advanced ETL in Pricing and Valuation

In dynamic financial markets, well-informed decisions depend on efficient access to accurate pricing and valuation data. In this blog, we explore three ways to streamline the collection and delivery of accurate pricing and valuation data: standardization, normalization, and advanced ETL.

  1. Standardization

Managing daily and monthly pricing data often involves the tedious task of collecting data sets from disparate sources, each of which resides in separate tables within a database, and occasionally is scattered across several databases. This fragmented approach is time-consuming and significantly hampers the efficiency of data retrieval for pricing and valuation.

One way the latest pricing and valuation tools address this challenge is through rigorous standardization. Data standardization essentially converts the structure of different datasets into a common format after data is collected from various sources but before it is loaded into a centralized system.

By creating a centralized and unified data repository, new pricing and valuation tools simplify access to reliable pricing data. The central hub becomes the single point of access for all pricing and valuation data, allowing faster and more seamless retrieval from various sources with just one query. As a result, standardization can significantly reduce the time and effort required to gather this vital information.

  1. Normalization

Beyond standardization, the path to higher efficiency lies in the normalization of consolidated pricing data. Normalization entails establishing a consistent set of attributes that apply universally across diverse data sources. These attributes may include bid, mid, and ask prices as well as standardized security identifiers like CUSIP and ISIN.

Normalization establishes a uniform structure for all data sets, making pricing and valuation data more accessible and user-friendly. The end result of effective normalization is a highly efficient pricing data retrieval system that simplifies the broader investment decision-making process.

  1. Advanced ETL

Extract, transform, and load (ETL) refers to the process of combining data from multiple sources into a large, central repository called a data warehouse. ETL uses well-defined rules to clean and organize raw data and prepare it for further analysis. When it comes to pricing and valuation data, advanced ETL capabilities are extremely important because they ensure the data sets are received by downstream applications are not only accessible but also reliable, consistent, and ready for in-depth analysis.

One example of how advanced ETL delivers analysis-ready data is its ability to apply transformation rules to input data, such as calculating the average of bid and ask prices for specific securities. With advanced ETL capabilities, the foundation of trust is laid. Advanced ETL effectively guarantees that pricing data furnished to the pricing and valuation tool is of the highest quality, having undergone rigorous transformations to ensure consistency and reliability.

In buy-side firms, efficient access to accurate pricing data is non-negotiable. The IVP Pricing and Valuation Automation Solution makes this possible, providing all of these cutting-edge capabilities. With the help of standardization, normalization, and advanced ETL capabilities, buy-side firms gain what is necessary to make better decisions more efficiently and gain a competitive edge.

For more information on how the IVP Pricing and Valuation Automation Solution helps ensure a smoother pricing process, please contact sales@ivp.in.

Pricing and Valuation Automation Solution

This solution provides pricing and valuation automation, connecting funds to leading pricing data vendors and brokers. It also provides a flexible, configurable pricing engine that caters to any pricing process. IVP’s solution is designed to automate and streamline the pricing and valuation process, which traditionally involves time-consuming tasks like data collection, rules application, and pricing tests, efficiently retrieving data from vendors and brokers, applying waterfall pricing rules, and ensuring that prices meet threshold checks. This includes handling highly illiquid securities and those from exotic asset classes.

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