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What is Integrated Business Planning (IBP)?

IBM Journey to AI blog

By having real-time data at their fingertips, decision-makers can adjust their strategies, allocate resources accordingly, and capitalize on the unexpected spike in demand, ensuring customer satisfaction while maximizing revenue. Data integration and analytics IBP relies on the integration of data from different sources and systems.

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What exactly is Data Profiling: It’s Examples & Types

Pickl AI

Accordingly, the need for Data Profiling in ETL becomes important for ensuring higher data quality as per business requirements. The following blog will provide you with complete information and in-depth understanding on what is data profiling and its benefits and the various tools used in the method.

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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

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Transform raw insurance data into CSV format acceptable to Neptune Bulk Loader , using an AWS Glue extract, transform, and load (ETL) job. When the data is in CSV format, use an Amazon SageMaker Jupyter notebook to run a PySpark script to load the raw data into Neptune and visualize it in a Jupyter notebook.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Learn more about the benefits of data fabric and IBM Cloud Pak for Data.

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Who is a BI Developer: Role, Responsibilities & Skills

Pickl AI

It is the process of converting raw data into relevant and practical knowledge to help evaluate the performance of businesses, discover trends, and make well-informed choices. Data gathering, data integration, data modelling, analysis of information, and data visualization are all part of intelligence for businesses.

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Warehousing: Amazon Redshift, Google BigQuery, etc.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.