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Supply Chain Analytics: Opportunities in Data Analysis and Business Intelligence

Altexsoft

diversity of sales channels, complex structure resulting in siloed data and lack of visibility. These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development.

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Top Data Science experts you should know about

Apiumhub

Borba has been named a top Big Data and data science influencer and expert several times. He has also been named a top influencer in machine learning, artificial intelligence (AI), business intelligence (BI), and digital transformation. Jen Stirrup is a top influencer in Big Data and Business Intelligence.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

Altexsoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

Altexsoft

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

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Analytics Maturity Model: Levels, Technologies, and Applications

Altexsoft

We will describe each level from the following perspectives: differences on the operational level; analytics tools companies use to manage and analyze data; business intelligence applications in real life; challenges to overcome and key changes that lead to transition. Introducing data engineering and data science expertise.

Analytics 102
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Data Lakehouse: Concept, Key Features, and Architecture Layers

Altexsoft

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Data lake architecture example. Poor data quality, reliability, and integrity.

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Big Data Analytics: How It Works, Tools, and Real-Life Applications

Altexsoft

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc.