Netflix Tech

FEBRUARY 14, 2025

The data collected feeds into a comprehensive quality dashboard and supports a tiered threshold-based alerting system. This approach will enhance efficiency, reduce manual oversight, and ensure a higher standard of data integrity.

Kafka 66

Kafka Datasets Metadata Utilities 66

Databand.ai

MAY 30, 2023

Data quality refers to the degree of accuracy, consistency, completeness, reliability, and relevance of the data collected, stored, and used within an organization or a specific context. High-quality data is essential for making well-informed decisions, performing accurate analyses, and developing effective strategies.

Data Cleanse 85

Data Cleanse Datasets Data Governance Data Validation 85

Cloudera

JUNE 2, 2022

Companies have not treated the collection, distribution, and tracking of data throughout their data estate as a first-class problem requiring a first-class solution. Instead they built or purchased tools for data collection that are confined with a class of sources and destinations.

Systems 104

Systems Data Lake Google Cloud Cloud 104

Striim

FEBRUARY 26, 2025

new Intercom Reader makes it even easier by enabling seamless real-time data integration from the Intercom platform into your analytics systems. It captures the necessary data and emits WAEvents, which can be propagated to any supported target systems , such as Google BigQuery, Snowflake, or Microsoft Azure Synapse. Striim 5.0s

Data Integration 40

Data Integration Data Collection Data Security Cloud 40

Cloudera

APRIL 15, 2019

While Cloudera Flow Management has been eagerly awaited by our Cloudera customers for use on their existing Cloudera platform clusters, Cloudera Edge Management has generated equal buzz across the industry for the possibilities that it brings to enterprises in their IoT initiatives around edge management and edge data collection.

Management 17

Management Data Ingestion Data Collection Government 17

Data Engineering Podcast

MAY 27, 2018

In this episode CTO and co-founder of Alooma, Yair Weinberger, explains how the platform addresses the common needs of data collection, manipulation, and storage while allowing for flexible processing.

Data Pipeline 100

Data Pipeline MongoDB Google Cloud Scala 100

Data Engineering Podcast

JULY 8, 2018

Summary Data integration and routing is a constantly evolving problem and one that is fraught with edge cases and complicated requirements. The Apache NiFi project models this problem as a collection of data flows that are created through a self-service graphical interface. How is that data collected and managed?

Building 100

Building Transportation Kafka Java 100

Data Engineering Podcast

NOVEMBER 20, 2022

What are the biggest data-related challenges that you face (technically or organizationally)? How does that influence your approach to instrumentation/data collection in the end-user experience? Can you describe the current architecture of your data platform? Multiplayer games are very sensitive to latency.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Towards Data Science

DECEMBER 4, 2023

Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g. Data Lake & Data Integration We’ll face our first challenge while we integrate and consolidate everything in a single place.

Data Engineer 98

Data Engineer Data Engineering Engineering Data Lake 98

U-Next

MARCH 7, 2023

This entails locating and correcting any blank or incomplete fields, eliminating duplicates, and checking the data’s accuracy. You can use automated systems to gather, analyze, and combine data from several sources into a coherent data collection. Salesforce’s CDP is one example.

Bytes 98

Bytes Media Data Data Collection 98

Cloudera

NOVEMBER 19, 2020

Cloudera Data Platform (CDP) is a solution that integrates open-source tools with security and cloud compatibility. Governance: With a unified data platform, government agencies can apply strict and consistent enterprise-level data security, governance, and control across all environments.

Government 119

Government Machine Learning Algorithm Raw Data 119

Precisely

MAY 24, 2023

Securities and Exchange Commission (SEC) regulations requiring public companies to report climate related-risks and emissions data – regardless of when it becomes final. Secondly, it’s critical to ensure that ESG reporting is being powered by accurate, consistent, and contextual data, as well as being supported with the right expertise.

Data Integration 52

Data Integration Government Data Collection Consulting 52

Cloudera

FEBRUARY 4, 2019

With the rise of streaming architectures and digital transformation initiatives everywhere, enterprises are struggling to find comprehensive tools for data management to handle high volumes of high-velocity streaming data. CDF can do this within a common framework that offers unified security, governance and management.

Data Ingestion 73

Data Ingestion Retail Kafka Data Lake 73

Monte Carlo

APRIL 27, 2023

While these bundled solutions quickly rose in popularity for marketing organizations over the past decade, questions lingered in their supporting data teams’ minds as to whether these were actually the right solution for collecting and activating customer data.

Data Warehouse 72

Data Warehouse Data Collection Architecture Data Storage 72

The Modern Data Company

FEBRUARY 2, 2024

Picture transforming the way we handle data to the point where launching a data application in just four weeks isn’t just a dream, but a practical reality. DataOS® streamlines every step of the development process, from the initial data collection right through to the final deployment of the application.

Raw Data 75

Raw Data Utilities Government Data 75

Striim

SEPTEMBER 11, 2024

Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making. These data sources serve as the starting point for the pipeline, providing the raw data that will be ingested, processed, and analyzed.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Netflix Tech

MARCH 25, 2019

Data Landscape Design Goals At the project inception stage, we defined a set of design goals to help guide the architecture and development work for data lineage to deliver a complete, accurate, reliable and scalable lineage system mapping Netflix’s diverse data landscape.

Building 90

Building Metadata Transportation Data Ingestion 90

Workfall

MARCH 7, 2023

Yew offers Rust’s rich type ecosystem which can be a great tool when it comes to ensuring data integrity on the client side. This is where form handling comes into play. What Is Form Handling?

PostgreSQL 79

PostgreSQL Database AWS Data Collection 79

Striim

JULY 10, 2024

Data Collection and Integration: Data is gathered from various sources, including sensor and IoT data, transportation management systems, transactional systems, and external data sources such as economic indicators or traffic data. Here’s the process.

Management 52

Management Transportation Machine Learning High Quality Data 52

Knowledge Hut

JULY 26, 2023

Biases can arise from various factors such as sample selection methods, survey design flaws, or inherent biases in data collection processes. Bugs in Application: Errors or bugs in data collection, storage, and processing applications can compromise the accuracy of the data.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

AltexSoft

MAY 12, 2022

Audio data transformation basics to know. Before diving deeper into processing of audio files, we need to introduce specific terms, that you will encounter at almost every step of our journey from sound data collection to getting ML predictions. One of the largest audio data collections is AudioSet by Google.

Machine Learning 122

Machine Learning Building Deep Learning Datasets 122

Precisely

SEPTEMBER 6, 2023

However, fewer than half of survey respondents rate their trust in data as “high” or “very high.” ” Poor data quality impedes the success of data programs, hampers data integration efforts, limits data integrity causing big data governance challenges.

Data Governance 52

Data Governance Big Data Government Unstructured Data 52

AltexSoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Process 69

Process Data Lake Metadata Data Warehouse 69

Cloudera

DECEMBER 22, 2017

This mountain of data holds a gold rush of opportunities for marketers to truly engage with their consumers, just as long as they can effectively mine through all that data and make sense of what really matters. To tackle this, it is worth considering the frequency of data being collected. Time is of the essence.

Data Mining 40

Data Mining Data Collection Data Integration Data 40

Databand.ai

AUGUST 30, 2023

In a world where organizations rely heavily on data observability for informed decision-making, effective data testing methods are crucial to ensure high-quality standards across all stages of the data lifecycle—from data collection and storage to processing and analysis.

Data Validation 52

Data Validation Data Integration Data Database 52

Ascend.io

NOVEMBER 21, 2023

More importantly, we will contextualize ELT in the current scenario, where data is perpetually in motion, and the boundaries of innovation are constantly being redrawn. This approach ensures that only processed and refined data is housed in the data warehouse, leaving the raw data outside of it. What Is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Hevo

JUNE 26, 2024

Organizations deal with data collected from multiple sources, which increases the complexity of managing and processing it. Oracle offers a suite of tools that helps you store and manage the data, and Apache Spark enables you to handle large-scale data processing tasks.

Data Collection 52

Data Collection Data Data Process Management 52

Precisely

JULY 25, 2023

As we work with SAP customers, Precisely has identified three core needs: Agility Speed Improved data integrity Agility Today, companies must be able to pivot quickly, adjusting to disruptions in the marketplace as soon as they occur.

Data Process 52

Data Process Process Data Data Integration 52

Cloudera

MAY 9, 2019

Data readiness – These set of metrics help you measure if your organization is geared up to handle the sheer volume, variety and velocity of IoT data. It is meant for you to assess if you have thought through processes such as continuous data ingestion, enterprise data integration and data governance.

Manufacturing 56

Manufacturing Data Ingestion Architecture Data Governance 56

Knowledge Hut

SEPTEMBER 27, 2023

Both Microsoft Power BI and Salesforce are industry leaders, each with distinct strengths in data management and decision support. Power BI is a robust data analytics tool, that enable analysis, dynamic dashboards, and seamless data integration. Functionality Data visualisation, trend prediction, creating reports etc.

BI 52

BI Datasets Data Security Data Analysis 52

ThoughtSpot

OCTOBER 18, 2024

Step 3: Implementing a data pipeline To automate the data collection and processing, we integrated a Jenkins job that runs hourly. This job aggregates the parsed JSON data, performs necessary transformations, and pushes the resulting data to a Cloud Data Warehouse (CDW).

Building 52

Building Process Pipeline-centric Database-centric 52

Databand.ai

JULY 6, 2023

These anomalies can significantly impact data analysis, leading to incorrect or misleading insights. Unintentional anomalies are data points that deviate from the norm due to errors or noise in the data collection process. This is part of a series of articles about data integrity.

Datasets 52

Datasets Algorithm Machine Learning Data Analysis 52

Striim

OCTOBER 11, 2024

Whether you’re in the healthcare industry or logistics, being data-driven is equally important. Here’s an example: Suppose your fleet management business uses batch processing to analyze vehicle data. Modern pipelines incorporate Exactly-Once Processing (E1P) to ensure data integrity.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Knowledge Hut

MARCH 29, 2024

In Java, a fail-fast iterator detects and throws a ConcurrentModificationException if the base collection changes structurally while iterating. It provides immediate notification of any concurrent changes, preserving data integrity by preventing potential errors. Enables concurrent modifications during iteration.

Java 52

Java Programming Data Integration Programming Language 52

Knowledge Hut

JANUARY 3, 2024

Qualitative data collection is the collection of descriptive and conceptual findings through questionnaires, interviews, or observation. Types of qualitative data include binary, nominal, and ordinal. It produces non-numerical data. Thus, these are the most common qualitative data analysis methods.

Data Collection 52

Data Collection Hospitality Data Analysis Datasets 52

Cloudera

JUNE 6, 2019

Lakshmi Randall is Director of Product Marketing at Cloudera, the enterprise data cloud company. Previously, she was a Research Director at Gartner ( News – Alert ) covering Data Warehousing, Data Integration, Big Data, Information Management, and Analytics practices. Learn more about Cloudera’s platform here.

Metadata 86

Metadata Data Lake Cloud Big Data 86

AltexSoft

SEPTEMBER 23, 2021

A data hub is a central mediation point between various data sources and data consumers. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. An ETL approach in the DW is considered slow, as it ships data in portions (batches.)

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52