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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

You may not even know exactly which path you should pursue, since some seemingly similar fields in the data technology sector have surprising differences. We decided to cover some of the most important differences between Data Mining vs Data Science in order to finally understand which is which. What is Data Science?

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5 Data Mining Tips to Leverage the Benefits of Surveys

Smart Data Collective

Well, if you are someone who has loads of data and aren’t using it for your surveys and you would love to learn more on how to use it, don’t go anywhere because, in this article, we will show you data mining tips you can use to leverage your surveys. 5 data mining tips for leveraging your surveys.

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What is business intelligence? Transforming data into business insights

CIO

A strong BI strategy can deliver accurate data and reporting capabilities faster to business users to help them make better business decisions in a more timely fashion. Increased competitive advantage: A sound BI strategy can help businesses monitor their changing market and anticipate customer needs.

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An Important Guide To Unsupervised Machine Learning

Smart Data Collective

Overall, unsupervised algorithms get to the point of unspecified data bits. Clustering – Exploration of Data. Cluster analysis is aimed at classifying objects into groups called clusters on the basis of the similarity criteria. Overall, clustering is a common technique for statistical data analysis applied in many areas.

Learning 338
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What is data architecture? A framework to manage data

CIO

Shared data assets, such as product catalogs, fiscal calendar dimensions, and KPI definitions, require a common vocabulary to help avoid disputes during analysis. Curate the data. Data architecture components A modern data architecture consists of the following components, according to IT consulting firm BMC : Data pipelines.

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Python for Business: Optimize Pre-Processing Data for Decision-Making

Smart Data Collective

Therefore, if you don’t preprocess the data before applying it in the machine learning or AI algorithms, you are most likely to get wrong, delayed, or no results at all. Hence, data preprocessing is essential and required. Python as a Data Processing Technology. Advantages and Disadvantages of Data Preprocessing in Python.

Business 342
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8 tips for unleashing the power of unstructured data

CIO

Unstructured data resources can be extremely valuable for gaining business insights and solving problems. Organizations that become skilled in tapping these vast information resources can gain a significant advantage in delivering actionable insights to key business processes. Another key to success is to prioritize data quality.

Gaming 488