Remove Deep Learning Remove Forecasting Remove Optimization Remove Unstructured Data
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The Rise of Unstructured Data

Cloudera

The International Data Corporation (IDC) estimates that by 2025 the sum of all data in the world will be in the order of 175 Zettabytes (one Zettabyte is 10^21 bytes). Most of that data will be unstructured, and only about 10% will be stored. Here we mostly focus on structured vs unstructured data.

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

The main difference being that while KNN makes assumptions based on data points that are closest together, LOF uses the points that are furthest apart to draw its conclusions. Unsupervised learning Unsupervised learning techniques do not require labeled data and can handle more complex data sets.

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Retailers can tap into generative AI to enhance support for customers and employees

IBM Big Data Hub

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time. trillion on retail businesses through 2029.

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Why Financial Services Firms are Championing Natural Language Processing

CIO Business Intelligence

In business, when a trend is forecast to grow by more than 3000% and generate cost savings of $7.3 NLP solutions can be used to analyze the mountains of structured and unstructured data within companies. Ready to evolve your analytics strategy or improve your data quality? NLP will account for $35.1 Putting NLP to Work.

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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. One study forecasts that the market will be worth $23.8 While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes.

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The most valuable AI use cases for business

IBM Big Data Hub

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. See what’s ahead AI can assist with forecasting.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

One ride-hailing transportation company uses big data analytics to predict supply and demand, so they can have drivers at the most popular locations in real time. The company also uses data science in forecasting, global intelligence, mapping, pricing and other business decisions.