Remove Data Analytics Remove Data Warehouse Remove Optimization Remove Unstructured Data
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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. 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. Data Warehouse.

Data Lake 106
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Understanding Structured and Unstructured Data

Sisense

Different types of information are more suited to being stored in a structured or unstructured format. Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both.

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Business Intelligence vs Data Science vs Data Analytics

FineReport

If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. What is Data Science? Typical tools for data science: SAS, Python, R.

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. The retailer uses these insights to optimize inventory levels, reduce costs and enhance efficiency.

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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 135
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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 130
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Understanding Social And Collaborative Business Intelligence

datapine

Let’s picture an ambiance where business users can make use of a business intelligence and analysis portal and view the popular data that can be rated, shared, and commented on. Interesting Read: THE DIFFERENT STAGES IN DATA ANALYTICS, AND WHERE DO YOU FIT IT IN AI AND ML ACTIVITIES? EXPERT OPINION]. Summing Up.