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Best BI Tools For 2024 You Need to Know

FineReport

In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. Harnessing the power of advanced APIs, automation, and AI, these tools simplify data compilation, organization, and visualization, empowering users to extract actionable insights effortlessly.

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

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What is Data Mapping?

Jet Global

Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation. Data mapping is important for several reasons.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. But first, let’s define what data quality actually is. 4 – Data Reporting.

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

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How to Aggregate Global Data from the Coronavirus Outbreak

Sisense

In this article, we discuss how this data is accessed, an example environment and set-up to be used for data processing, sample lines of Python code to show the simplicity of data transformations using Pandas and how this simple architecture can enable you to unlock new insights from this data yourself.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.