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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. In business analytics, this is the purview of business intelligence (BI). It is frequently used for risk analysis.

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Best BI Tools Examples for 2024: Business Intelligence Software

FineReport

Through interactive dashboards , these tools empower users across various departments to access and interpret data effectively. By leveraging advanced analytics capabilities, businesses can uncover hidden opportunities and potential risks within their datasets, allowing them to proactively address challenges and capitalize on emerging trends.

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How IBM Planning Analytics can help fix your supply chain

IBM Big Data Hub

Having the ability to build and use models in this way is fundamental to managing supply chain and financial risk through activities like “what-if scenario planning”, as explained in this blog post. As such, planning becomes a continuous rolling activity as the lines between “plan”, “budget” and “forecast” are blurred.

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making.

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What Is The Difference Between Business Intelligence And Analytics?

datapine

We already saw earlier this year the benefits of Business Intelligence and Business Analytics. In an article tackling BI and Business Analytics, Better Buys asked seven different BI pros what their thoughts were on the difference between business intelligence and analytics. Confused yet?

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Business analytics in the age of disruption

IBM Big Data Hub

To navigate this constantly disrupted world, clients need more data, more collaboration and more assurances that they can act at the speed of business without risk. This situation persists across all areas of the business, and organizations have had to focus on new data applications to find a path towards success and resiliency.

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Moving beyond spreadsheets with IBM Planning Analytics

IBM Big Data Hub

My journey with IBM Planning Analytics started with an early morning phone call to tell me that a member of my team had died, suddenly and unexpectedly. Our teams relied heavily on his decades of expertise to help us plan and forecast strategically for the future. If there was ever an example of key-person risk, this was it.