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Data Science vs Data Analytics: Key Differences

Astera

Data Science Process Business Objective: This is where you start. You define the business objectives, assess the situation, determine the data science goals, and plan the project. It involves visualizing the data using plots and charts to identify patterns, trends, and relationships between variables.

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Making the switch from homegrown systems to PIM

Ntara

Wherever your data is stored between your enterprise resource planning (ERP) and your website or your distributors’ websites, let’s call this your “homegrown” solution. If this sounds like you, and you haven’t intentionally setup a PIM or other data management system, this article is for you.

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Making the switch from homegrown systems to PIM

Ntara

Wherever your data is stored between your enterprise resource planning (ERP) and your website or your distributors’ websites, let’s call this your “homegrown” solution. If this sounds like you, and you haven’t intentionally setup a PIM or other data management system, this article is for you.

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All You Need to Know About Data Aggregation

Astera

Data Aggregation Types and Techniques There are various types of data aggregation. Your requirements and how you plan to use the data will determine which approach suits your use case. Temporal As the name suggests, temporal aggregation summarizes data over specified time intervals.

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A Complete Guide to Data Analytics

Astera

Variability: The inconsistency of data over time, which can affect the accuracy of data models and analyses. This includes changes in data meaning, data usage patterns, and context. Visualization: The ability to represent data visually, making it easier to understand, interpret, and derive insights.

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Optimize SAP Data Analysis for a Sustainable Future

Insight Software

Improper load optimization: Often caused by inefficient planning and inadequate utilization of cargo space, leading to poor transportation efficiency such as half-full containers. Optimize for a greener future: Leverage insights to implement resource-saving technologies, optimize logistics, and source from sustainable suppliers.

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Use Automation and Analysis to De-Fog Your Supply Chain

Insight Software

The objective is clear: eradicate manual processes and static reports, gain oversight of supply chain data and generate insights that drive more business value. Dealing with multiple siloed operational data sources is killing your operational team’s productivity. Making strategic decisions backed by hard data.