The processing and analyzing of data records continuously rather than in batches. Generally, streaming analytics is useful for the types of data sources that send data in small sizes (often in kilobytes) in a continuous flow as the data is generated.
Published in Chapter:
Financial Analytics With Big Data
Leon Wang (Big Data Club, USA)
Copyright: © 2023
|Pages: 13
DOI: 10.4018/978-1-7998-9220-5.ch114
Abstract
Like in other industries, financial institutions are facing a new era of big data, which plays the leading role in transformation of financial and economic environment. This article dives into why big data is important in the financial field, and how the information it provides is useful and helpful to corporations and companies. Applying big data analytics provides financial firms with insight into how they can detect fraud, conduct real-time analytics, deal with risk, and direct customer portfolio. Specific personalized services can be offered for their customers via customer portfolio management, customer data management, and analytics, even with real-time analytics. Corporations can better forecast financial markets, trends, patters, and irregularities. Therefore, financial analytics has become a fundamental instrument for finance firms, professional, and individual investors, as well as financial researchers.