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

Ascend.io

JANUARY 2, 2024

But let’s be honest, creating effective, robust, and reliable data pipelines, the ones that feed your company’s reporting and analytics, is no walk in the park. From building the connectors to ensuring that data lands smoothly in your reporting warehouse, each step requires a nuanced understanding and strategic approach.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Cloudera

APRIL 9, 2021

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

Machine Learning 98

Machine Learning Manufacturing Data Collection Data Science 98

Ascend.io

JULY 28, 2023

Data pipelines are integral to business operations, regardless of whether they are meticulously built in-house or assembled using various tools. As companies become more data-driven, the scope and complexity of data pipelines inevitably expand. Ready to fortify your data management practice?

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52

Knowledge Hut

JUNE 26, 2023

From exploratory data analysis (EDA) and data cleansing to data modeling and visualization, the greatest data engineering projects demonstrate the whole data process from start to finish. Data pipeline best practices should be shown in these initiatives. Which queries do you have?

Data Engineer 98

Data Engineer Data Engineering Coding Project 98

Netflix Tech

MARCH 25, 2019

You are about to make structural changes to the data and want to know who and what downstream to your service will be impacted. Finally, imagine yourself in the role of a data platform reliability engineer tasked with providing advanced lead time to data pipeline (ETL) owners by proactively identifying issues upstream to their ETL jobs.

Building 90

Building Metadata Transportation Data Ingestion 90

Data Engineering Weekly

OCTOBER 30, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Ingestion 52

Knowledge Hut

JANUARY 18, 2024

Let us now look into the differences between AI and Data Science: Data Science vs Artificial Intelligence [Comparison Table] SI Parameters Data Science Artificial Intelligence 1 Basics Involves processes such as data ingestion, analysis, visualization, and communication of insights derived.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Monte Carlo

MARCH 24, 2023

Data integrity issues can arise at multiple points across the data pipeline. We often refer to these issues as data freshness or stale data. For example: The source system could provide corrupt data or rows with excessive NULLs. Learn more in our blog post 9 Best Practices To Maintain Data Integrity.

Data Validation 52

Data Validation Data Integration Data Cleanse Data Pipeline 52

Ascend.io

JANUARY 10, 2024

This continuous adaptation ensures that your data management stays effective and compliant with current standards. The goal is to ensure your organization has the capability to process and prepare data effectively for your AI models. Your data pipeline platform should excel in collecting data from a wide array of sources.

Data Pipeline 52

Data Pipeline Government Data Governance Raw Data 52

Data Engineering Weekly

NOVEMBER 20, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today.

Data Engineer 52

Data Engineer Data Engineering Engineering Datasets 52

DareData

JULY 5, 2023

Users: Who are users that will interact with your data and what's their technical proficiency? Data Sources: How different are your data sources? Latency: What is the minimum expected latency between data collection and analytics? And what is their format?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Monte Carlo

MAY 25, 2023

Picture this: your data is scattered. Data pipelines originate in multiple places and terminate in various silos across your organization. Your data is inconsistent, ungoverned, inaccessible, and difficult to use. Some of the value companies can generate from data orchestration tools include: Faster time-to-insights.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

Data Engineering Weekly

NOVEMBER 13, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today.

Data Engineer 52

Data Engineer Data Engineering Engineering Kafka 52

ProjectPro

AUGUST 24, 2021

Data Sourcing: Building pipelines to source data from different company data warehouses is fundamental to the responsibilities of a data engineer. So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. Google BigQuery receives the structured data from workers.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

Rockset

OCTOBER 26, 2022

One was to create another data pipeline that would aggregate data as it was ingested into DynamoDB. All in all, trying to make DynamoDB support fast analytics was a nightmare that would not end. And with the NFL season set to start in less than a month, we were in a bind.

SQL 52

SQL NoSQL Database Aggregated Data 52

ProjectPro

FEBRUARY 21, 2023

Knowledge of the definition and architecture of AWS Big Data services and their function in the data engineering lifecycle, including data collection and ingestion, data analytics, data storage, data warehousing, data processing, and data visualization.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Snowflake

APRIL 20, 2023

Data Pipelines Snowpipe Streaming – public preview While data generated in real time is valuable, it is more valuable when paired with historical data that helps provide context. The company’s data is highly accurate, which makes deriving insights easy and decision-making truly fact based.

Medical 59

Medical Retail Python Pharmaceutical 59

Monte Carlo

OCTOBER 5, 2023

Today’s modern approach to data governance is incredibly complex, with governance teams needing to oversee increasing volumes of data ingested from diverse sources, dispersed storage across cloud-based infrastructures, and an appetite for democratized access across the organization.

Government 52

Government Data Governance Data Cloud Storage 52

U-Next

JUNE 29, 2022

Data must be consumed from many sources, translated and stored, and then processed before being presented understandably. However, the benefits might be game-changing: a well-designed big data pipeline can significantly differentiate a company. Data ingestion can be divided into two categories: .

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

phData: Data Engineering

JANUARY 3, 2022

The role of a data engineer is going to vary depending on the particular needs of your organization. It’s the role of a data engineer to store, extract, transform, load, aggregate, and validate data. This involves: Building data pipelines and efficiently storing data for tools that need to query the data.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Governance 52

AltexSoft

MAY 14, 2021

Big Data analytics encompasses the processes of collecting, processing, filtering/cleansing, and analyzing extensive datasets so that organizations can use them to develop, grow, and produce better products. Big Data analytics processes and tools. Data ingestion. Let’s take a closer look at these procedures.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Monte Carlo

FEBRUARY 15, 2023

This article will define in simple terms what a data warehouse is, how it’s different from a database, fundamentals of how they work, and an overview of today’s most popular data warehouses. What is a data warehouse? Finally, where and how the data pipeline broke isn’t always obvious. They need to be transformed.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Steps for Data preparation. How can AWS solve Big Data Challenges?

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. Another reason to use PySpark is that it has the benefit of being able to scale to far more giant data sets compared to the Python Pandas library.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

DECEMBER 28, 2021

Moreover, Spark SQL makes it possible to combine streaming data with a wide range of static data sources. For example, Amazon Redshift can load static data to Spark and process it before sending it to downstream systems. Streaming, batch, and interactive processing pipelines can share and reuse code and business logic.

Architecture 52

Architecture Kafka Java Scala 52

Rockset

DECEMBER 17, 2020

Overview of the Customer 360 App Our app will make use of real-time data on customer orders and events. We’ll use Rockset to get data from different sources and run analytical queries that power our app in Retool. For our example, DynamoDB will store customers’ orders, and we will get the customer_events stream through Amazon Kinesis.

Building 40

Building SQL Aggregated Data Database 40

Rockset

DECEMBER 19, 2023

Additionally, some systems utilize pre-computed lists, such as those generated by data pipelines that identify the top 100 most popular content pieces globally, serving as another form of candidate generator. Moreover, the system is latency-bound, often needing to process these millions of data points within tens of milliseconds.

Systems 52

Systems Machine Learning Deep Learning Media 52

U-Next

SEPTEMBER 23, 2022

The fast development of digital technologies, IoT goods and connectivity platforms, social networking apps, video, audio, and geolocation services has created the potential for massive amounts of data to be collected/accumulated. In this post, we’ll explain each Big Data component along with the Big Data ecosystem.

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

MAY 31, 2021

Below is a list of Big Data project ideas and an idea of the approach you could take to develop them; hoping that this could help you learn more about Big Data and even kick-start a career in Big Data. Organizations constantly run their operations so that every department has its data.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

OCTOBER 20, 2021

Having multiple data integration routes helps optimize the operational as well as analytical use of data. Experimentation in production Big Data Data Warehouse for core ETL tasks Direct data pipelines Tiered Data Lake 4. Data: Data Engineering Pipelines Data is everything.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52