What is Alternative Data? Uses, Types & Dataset Examples

Alternative Data Explained

Use Cases

Use Case 1: Investment Research and Analysis

Alternative data is widely used in investment research and analysis to gain insights into various industries and companies. By analyzing alternative data sources such as social media sentiment, web scraping, satellite imagery, credit card transactions, and more, investors can make more informed decisions about their investment strategies. This data can provide valuable information about consumer behavior, market trends, and company performance, helping investors identify potential investment opportunities and risks.

Use Case 2: Risk Management and Fraud Detection

Alternative data is also utilized in risk management and fraud detection across various industries. By incorporating alternative data sources into risk models, organizations can better assess and mitigate potential risks. For example, credit card companies can analyze transaction data to identify fraudulent activities and prevent financial losses. Insurance companies can leverage alternative data to assess the risk profile of policyholders and determine appropriate premiums. By utilizing alternative data, organizations can enhance their risk management practices and improve fraud detection capabilities.

Use Case 3: Supply Chain Optimization

Alternative data plays a crucial role in supply chain optimization by providing real-time insights into various aspects of the supply chain. Companies can leverage alternative data sources such as IoT sensors, weather data, and social media trends to monitor and predict demand patterns, optimize inventory levels, and improve logistics operations. By analyzing alternative data, organizations can make data-driven decisions to streamline their supply chain processes, reduce costs, and enhance overall operational efficiency.

Main Attributes of Alternative Data

Alternative data refers to non-traditional information that is used to gain insights and make informed decisions. It can be sourced from a variety of alternative data sources such as social media, satellite imagery, web scraping, credit card transactions, and more. The attributes of alternative data can vary depending on the specific dataset, but some common attributes include time-stamped data, unstructured data, high volume and velocity, diverse data types, and the ability to provide real-time or near real-time information. These attributes enable alternative data to offer unique perspectives and complement traditional data sources. Here’s a table of the main attributes you might find on Alternative Datasets:

How are Alternative Data products priced?

Alternative datasets are typically priced based on various factors such as the quality, uniqueness, and relevance of the data. The pricing structure for alternative datasets can vary significantly depending on the provider and the specific dataset. Some datasets may be priced on a subscription basis, where users pay a recurring fee to access the data for a certain period of time. Other datasets may be priced on a per-use basis, where users pay a fee each time they access or download the data. Additionally, the pricing may also depend on the size and complexity of the dataset, with larger and more comprehensive datasets generally commanding higher prices. Overall, the pricing of alternative datasets is determined by the value and insights that the data can provide to users in making informed investment decisions.