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Content analytics is the act of applying business intelligence (BI) and business analytics (BA) practices to digital content. Companies use content analytics software to provide visibility into the amount of content that is being created, the nature of that content and how it is used.
A company produces two types of content: structured and unstructured. Structured content resides in a database. Unstructured content can be found throughout the business. It can be text-based, as in the case of emails, office documents and Web documents -- or non-text-based, such as voice, images or video. Content analytics software uses natural language queries, trends analysis, contextual discovery and predictive analytics to uncover patterns and trends across a company’s unstructured content.
The goal of content analysis is to gain new insights for improved decision-making. For example, a pattern in unstructured content may explain a trend in structured data, or vice versa. Content analytics can also help companies better manage information lifecycle management (ILM) chains by creating relevant cost and consumption metrics. With business metrics in place, companies can identify which digital content is most value and adjust their investments in storage and future analytics accordingly.
When it comes to a predictive analytics tool, Birst BI may the best solution for your enterprise, especially if you're trying to connect centralized teams to decentralized teams in the organization.