Data Engineering Weekly

JANUARY 15, 2025

They are responsible for designing, implementing, and maintaining robust, scalable data pipelines that transform raw unstructured data—text, images, videos, and more—into high-quality, AI-ready datasets. Validate synthetic data to ensure it is representative, diverse, and suitable for the intended AI applications.

Data Engineering 63

Data Engineering Data Engineer Unstructured Data Engineering 63

DataKitchen

FEBRUARY 17, 2025

Manually writing tests limits the scope of what gets tested and can introduce biases, making it difficult to get a complete picture of data quality. Organizations that fail to prioritize data quality testing risk compromising their data integrity, affecting their ability to make informed business decisions.

SQL 74

SQL Python Government Data Engineering 74

Edureka

JULY 5, 2024

Tableau Prep is a fast and efficient data preparation and integration solution (Extract, Transform, Load process) for preparing data for analysis in other Tableau applications, such as Tableau Desktop. simultaneously making raw data efficient to form insights.

Data Preparation 40

Data Preparation Process BI ETL Tools 40

Striim

MARCH 21, 2025

With instant elasticity, high-performance, and secure data sharing across multiple clouds , Snowflake has become highly in-demand for its cloud-based data warehouse offering. As organizations adopt Snowflake for business-critical workloads, they also need to look for a modern data integration approach.

Data Warehouse 52

Data Warehouse MongoDB MySQL Hadoop 52

ThoughtSpot

MARCH 5, 2024

Schedule refreshes to keep ThoughtSpot analytics up to date by automatically incorporating new data into Liveboards, NL Searches, and Answers. Simplifiy multi-structured data integration by federating JSON, XML, and other formats through Snowflake for analysis.

BI 111

BI Datasets SQL Raw Data 111

Christophe Blefari

APRIL 8, 2023

Microsoft data integration new capabilities — Few months ago I've entered the Azure world. Today, Microsoft announces new low-code capabilities for Power Query in order to do "data preparation" from multiple sources. Not really without pain.

Pipeline-centric 130

Pipeline-centric Database-centric Algorithm Data 130

Christophe Blefari

APRIL 8, 2023

Microsoft data integration new capabilities — Few months ago I've entered the Azure world. Today, Microsoft announces new low-code capabilities for Power Query in order to do "data preparation" from multiple sources. Not really without pain.

Pipeline-centric 130

Pipeline-centric Database-centric Algorithm Data 130

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

AltexSoft

MAY 12, 2022

Particularly, we’ll explain how to obtain audio data, prepare it for analysis, and choose the right ML model to achieve the highest prediction accuracy. But first, let’s go over the basics: What is the audio analysis, and what makes audio data so challenging to deal with. Audio data preparation.

Machine Learning 122

Machine Learning Building Deep Learning Healthcare 122

Precisely

JULY 18, 2024

Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata. As data grows exponentially, so do the complexities of managing and leveraging it to fuel AI and analytics.

Data Management 52

Data Management Management Metadata Database-centric 52

RandomTrees

AUGUST 22, 2024

Artificial Intelligence and Machine Learning Integration AI and machine learning are becoming increasingly central to BI solutions. IoT and Edge Analytics The proliferation of Internet of Things (IoT) devices is generating massive amounts of data.

Business Intelligence 52

Business Intelligence BI Data Preparation Machine Learning 52

AltexSoft

OCTOBER 30, 2021

A data scientist takes part in almost all stages of a machine learning project by making important decisions and configuring the model. Data preparation and cleaning. Final analytics are only as good and accurate as the data they use. Data warehousing.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Precisely

SEPTEMBER 12, 2024

Companies want to spend less time on data preparation and more time deriving insights from easy-to-access location reports. Spatial analytics help you discover relationships that empower key business initiatives, and it all starts with accurate, consistent, and complete location data. Enabling competitive advantage.

Food 64

Food Insurance Data Science Data 64

Knowledge Hut

JANUARY 29, 2024

Google DataPrep: A data service provided by Google that explores, cleans, and prepares data, offering a user-friendly approach. Data Wrangler: Another data cleaning and transformation tool, offering flexibility in data preparation.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Precisely

DECEMBER 4, 2023

Read our Article Telecom Data: Unlock Your Data Integrity Potential Telecommunications providers have led the way in using spatial analytics for network planning and strategic decision-making. They also need a strong foundation of data science to underpin those efforts.

Telecommunication 64

Telecommunication Data Science Data Integration Data Preparation 64

DataKitchen

DECEMBER 9, 2022

DataOps involves close collaboration between data scientists, IT professionals, and business stakeholders, and it often involves the use of automation and other technologies to streamline data-related tasks. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

Machine Learning 52

Machine Learning Data Preparation Government Data Analytics 52

Precisely

FEBRUARY 12, 2024

This shortfall in effective data governance inhibits visibility and transparency. Data integration and data integrity are lacking. Before business users can tap into the value of their data to deliver positive outcomes, that data must be complete, contextual, timely, accurate, and available.

Data Governance 64

Data Governance Government Telecommunication Machine Learning 64

Confluent

JUNE 18, 2019

It involves many moving parts, from data preparation to building indexing and query pipelines. Luckily, this task looks a lot like the way we tackle problems that arise when connecting data. Schema evolution is inevitable in all data integration situations, and search is no exception. Schema evolution.

Architecture 97

Architecture Building Kafka Database-centric 97

RandomTrees

FEBRUARY 6, 2024

Necessity for automation : Gen AI has the capacity to automate multiple data engineering processes, such as data integration, transformation, and pipeline creation, enabling data engineers to allocate their time to more valuable endeavors.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

JANUARY 25, 2024

Data cleaning is like ensuring that the ingredients in a recipe are fresh and accurate; otherwise, the final dish won't turn out as expected. It's a foundational step in data preparation, setting the stage for meaningful and reliable insights and decision-making. Let's explore these essential tools.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

FreshBI

SEPTEMBER 11, 2023

Power BI, Microsoft's cutting-edge business analytics solution, empowers users to visualize data and seamlessly distribute insights. However, the complex process of data preparation, modeling, and report creation can be time and resource consuming, especially when handling intricate datasets.

BI 59

BI Consulting Datasets Data Ingestion 59

Knowledge Hut

OCTOBER 4, 2023

It is because they help you generate dynamic reports and feature data modeling, complete data comparison, and more. Understanding Power BI Requirements As I have mentioned before, Power BI is a revolutionary, remarkable program that enables high-speed data integration and the creation of plenty of reports.

BI 52

BI Systems Raw Data Data Preparation 52

Databand.ai

AUGUST 30, 2023

Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing, and maintaining data quality. There are several types of data testing tools. This is part of a series of articles about data quality.

Data Cleanse 52

Data Cleanse Data Validation Data Pipeline Datasets 52

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. SQL Server Integration Services (SSIS): You know it; your father used it.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. There are several types of data testing tools.

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

Rockset

DECEMBER 14, 2022

With the MSK integration, users do not need to build, deploy or operate any infrastructure components on the Kafka side. The integration is continuous so any new data in the Kafka topic will get indexed in Rockset, delivering an end-to-end data latency of around two seconds.

Kafka 52

Kafka MongoDB SQL AWS 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

APRIL 25, 2024

These technologies are necessary for data scientists to speed up and increase the efficiency of the process. The main features of big data analytics are: 1. Data wrangling and Preparation The idea of Data Preparation procedures conducted once during the project and performed before using any iterative model.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Ascend.io

AUGUST 16, 2023

The collection and preparation of data used for analytics are achieved by building data pipelines that ingest raw data and transform it into useful formats leveraging cloud data platforms like Snowflake, Databricks, and Google BigQuery. Changes in one pipeline often cascade down to different teams and projects.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Cloudera

MAY 16, 2019

The conference provides a useful opportunity to reflect on the rapid evolution we’ve seen in the Data Integration and Management space, much of it driven by the innovations that Cloudera and the open source community have been delivering. The traditional Data Warehouse ETL process has splintered into many smaller components.

Data Warehouse 40

Data Warehouse Government Data Preparation Data Governance 40

Knowledge Hut

NOVEMBER 3, 2023

Data Visualization It provides a wide range of networks, diagrams, and maps. Boasts an extensive library of customizable visuals for diverse data representation. Augmented Analytics Incorporates machine learning and AI for automated data preparation, insights, and suggestions.

BI 52

BI Cloud Retail Medical 52

Knowledge Hut

OCTOBER 30, 2023

This data and reports are generated and developed by Power BI developers. A Power BI developer is a business intelligence personnel who thoroughly understands business intelligence, data integration, data warehousing, modeling, database administration, and technical aspects of BI systems.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Knowledge Hut

MARCH 28, 2024

Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance. Develop data models, data governance policies, and data integration strategies. Familiarity with ETL tools and techniques for data integration.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

MAY 25, 2023

Some of the value companies can generate from data orchestration tools include: Faster time-to-insights. Automated data orchestration removes data bottlenecks by eliminating the need for manual data preparation, enabling analysts to both extract and activate data in real-time. Improved data governance.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

Striim

SEPTEMBER 4, 2024

It provides the infrastructure to ingest, process, and manage continuous data flows in real-time. This is where Striim comes into play, offering a robust platform designed to handle the complexities of stream processing and real-time data integration. Capturing schema changes from source systems and managing data drift.

Machine Learning 52

Machine Learning Datasets Data Systems 52

Knowledge Hut

APRIL 19, 2023

Talend: A commercial ETL tool that supports batch and real-time data integration.It provides connectors for data sources and symbols, as well as a visual interface for designing ETL pipelines. Informatica PowerCenter: A business ETL tool that supports batch and real-time data integration.

Data Warehouse 52

Data Warehouse Business Intelligence ETL Tools Data Pipeline 52

AltexSoft

MAY 14, 2021

Talend is an open-source data integration and data management platform that empowers users with facilitated, self-service data preparation. Talend is considered one of the most effective and easy-to-use data integration tools focusing on Big Data. Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78