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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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The Good and the Bad of Microsoft Power BI Data Visualization

Altexsoft

In our blog, we’ve been talking a lot about the importance of business intelligence (BI), data analytics, and data-driven culture for any company. Users can easily create a wide range of data-intensive, yet intelligible reports and dashboards and share obtained insights. What is Power used for? ranking (e.g.,

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ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

Altexsoft

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. ELT vs ETL. Order of process phases.

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The Good and the Bad of Apache Spark Big Data Processing

Altexsoft

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general.

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

Altexsoft

On top of that, new technologies are constantly being developed to store and process Big Data allowing data engineers to discover more efficient ways to integrate and use that data. You may also want to watch our video about data engineering: A short video explaining how data engineering works.

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Hotel Data Management: Solutions and Practices to Turn Information into a Valuable Asset

Altexsoft

Key performance metrics (KPIs) — such as Average Daily Rate (average price per room), occupancy rate (the percentage of available rooms), Revenue per Available Room (RevPAR). Previously, the only way data could get into the PMS was the manual input performed by a front-desk manager. Data processing in a nutshell and ETL steps outline.

Hotels 18