Snowflake

JULY 27, 2023

It also came with other advantages such as independence of cloud infrastructure providers, data recovery features such as Time Travel , and zero copy cloning which made setting up several environments — such as dev, stage or production — way more efficient.

Data Architecture 52

Data Architecture Architecture Building Structured Data 52

Monte Carlo

AUGUST 31, 2023

Understanding the “rise of data downtime” With a greater focus on monetizing data coupled with the ever present desire to increase data accuracy, we need to better understand some of the factors that can lead to data downtime. We’ll take a closer look at variables that can impact your data next.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Monte Carlo

JULY 27, 2023

These specialists are also commonly referred to as data reliability engineers. To be successful in their role, data quality engineers will need to gather data quality requirements (mentioned in 65% of job postings) from relevant stakeholders.

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

Maxime Beauchemin

JANUARY 20, 2017

Data modeling is changing Typical data modeling techniques — like the star schema  — which defined our approach to data modeling for the analytics workloads typically associated with data warehouses, are less relevant than they once were.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Databand.ai

JULY 5, 2023

They provide insights into the health of data integration processes, detect issues in real-time, and enable teams to optimize data flows. Data lake and data warehouse monitoring: These tools monitor the performance, storage, and access patterns of data lakes and data warehouses, ensuring optimal performance and data availability.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

Monte Carlo

OCTOBER 11, 2022

We’ll then discuss how they can be avoided with an organizational commitment to high-quality data. Imagine this You’re a data scientist with a swagger working on a predictive model to optimize a fast-growing company’s digital marketing spend. The data warehouse is a mess and devoid of semantic meaning.

IT 52

IT Datasets Data Warehouse Data Analysis 52

Ascend.io

FEBRUARY 28, 2024

While data engineering and Artificial Intelligence (AI) may seem like distinct fields at first glance, their symbiosis is undeniable. The foundation of any AI system is high-quality data. Here lies the critical role of data engineering: preparing and managing data to feed AI models.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Knowledge Hut

JUNE 28, 2023

Reporting, querying, and analyzing structured data to generate actionable insights. Data Sources Diverse and vast data sources, including structured, unstructured, and semi-structured data. Structured data from databases, data warehouses, and operational systems.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Data lakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Data Engineering Podcast

JULY 16, 2021

Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. No more scripts, just SQL.

High Quality Data 100

High Quality Data Data Engineering Data Engineer Coding 100

Edureka

FEBRUARY 7, 2023

They should also be proficient in programming languages such as Python , SQL , and Scala , and be familiar with big data technologies such as HDFS , Spark , and Hive. Learn programming languages: Azure Data Engineers should have a strong understanding of programming languages such as Python , SQL , and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

DataKitchen

NOVEMBER 4, 2021

It’s too hard to change our IT data product. Can we create high-quality data in an “answer-ready” format that can address many scenarios, all with minimal keyboarding? . “I I get cut off at the knees from a data perspective, and I am getting handed a sandwich of sorts and not a good one!”.

Process 98

Process Data Process Pharmaceutical Data Lake 98

Data Engineering Podcast

FEBRUARY 4, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Starburst : ![Starburst

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

Monte Carlo

AUGUST 8, 2023

From this perspective, the data validation process looks a lot like any other DataOps process. You should then document this information and even consider creating a data SLA. In these cases it is important to understand data lineage. The reliability of your data product is as strong as its weakest link.

Data Validation 52

Data Validation Data Pipeline SQL Data 52

DataKitchen

JANUARY 3, 2022

They need high-quality data in an answer-ready format to address many scenarios with minimal keyboarding. What they are getting from IT and other data sources is, in reality, poor-quality data in a format that requires manual customization. DataOps Process Hub.

Business Analyst 98

Business Analyst Data Lake Consulting Data Analytics 98

Data Engineering Podcast

JANUARY 21, 2024

In this episode Tasso Argyros, CEO of ActionIQ, gives a summary of the major epochs in database technologies and how he is applying the capabilities of cloud data warehouses to the challenge of building more comprehensive experiences for end-users through a modern customer data platform (CDP).

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Monte Carlo

AUGUST 17, 2021

Their artificial intelligence data-driven platform relies on high-quality data to make coverage recommendations for customers. Clearcover Clearcover is dedicated to making it easy and secure for car owners to save time and money on their insurance.

Insurance 40

Insurance Retail Data Pipeline Portfolio 40

ProjectPro

MAY 13, 2016

As the appetite for Hadoop and related big data technologies grows at an exponential rate, it is not out to spell the death of data warehousing. Data warehousing as a technology is evolving. Data Warehouse – Decide Which One to Use When Hadoop vs DataWarehouse Shocking Headlines like “Is data warehouse dead?”,

Data Warehouse 40

Data Warehouse Hadoop Unstructured Data Big Data 40

Striim

APRIL 30, 2024

Their strategic approach to adopting technological solutions, particularly through the integration of Striim for real-time data analytics, positions Kramp as a visionary in leveraging technology for business growth and efficiency in agriculture.

Google Cloud 52

Google Cloud High Quality Data Business Intelligence Data Warehouse 52

Airbnb Tech

NOVEMBER 28, 2023

However, for all of our uncertified data, which remained the majority of our offline data, we lacked visibility into its quality and didn’t have clear mechanisms for up-leveling it. How could we scale the hard-fought wins and best practices of Midas across our entire data warehouse?

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Monte Carlo

FEBRUARY 20, 2024

Choosing one tool over another isn’t just about the features it offers today; it’s a bet on the future of how data will flow within organizations. Matillion is an all-in-one ETL solution that stands out for its ability to handle complex data transformation tasks in all the popular cloud data warehouses.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Cloudera

OCTOBER 7, 2022

With this announcement, we welcome our customer data teams to streamline data transformation pipelines in their open data lakehouse using any engine on top of data in any format in any form factor and deliver high quality data that their business can trust. The Open Data Lakehouse .

Data Warehouse 83

Data Warehouse Data Lake Government High Quality Data 83

Monte Carlo

FEBRUARY 23, 2024

And this renewed focus on data quality is bringing much needed visibility into the health of technical systems. As generative AI (and the data powering it) takes center stage, it’s critical to bring this level of observability to where your data lives, in your data warehouse , data lake , or data lakehouse.

Systems 64

Systems Building Retail Data Lake 64

Monte Carlo

FEBRUARY 23, 2024

And this renewed focus on data quality is bringing much needed visibility into the health of technical systems. As generative AI (and the data powering it) takes center stage, it’s critical to bring this level of observability to where your data lives, in your data warehouse , data lake , or data lakehouse.

Systems 52

Systems Building Retail Data Lake 52

Picnic Engineering

DECEMBER 12, 2023

The rich context provided by our Snowflake-powered Data Warehouse enhances their performance, allowing us to create a robust feature set for training. Maintaining Data Quality Anybody working with machine learning knows the saying “Garbage in, Garbage out” because of one reason: it is true.

Machine Learning 52

Machine Learning Deep Learning Food High Quality Data 52

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Raw Data 70

Raw Data Data Business Intelligence High Quality Data 70

Edureka

FEBRUARY 27, 2023

Here are some of the common types: Data Warehouses: A data warehouse is a centralized repository of information that can be used for reporting and analysis. Data warehouses typically contain historical data that can be used to track trends over time.

Business Intelligence 52

Business Intelligence BI Data Mining Data Warehouse 52

Monte Carlo

FEBRUARY 8, 2024

How does it impact data warehouse/lakehouse performance? If you had an Airflow job that caused your data to fail, the real culprit wouldn’t be the data but a system issue. Or if a bad dbt model or data warehouse query change ultimately broke the data product downstream, that would be considered a code issue.

BI 59

BI Data Pipeline Data Warehouse Data 59

Data Engineering Weekly

NOVEMBER 13, 2022

It moved from the speculation to the data engineers understanding the benefit of it and asking when we can get the implementation soon. I met many data leaders about Data Contracts, my project Schemata, and how the extended version we are building can help them create high-quality data.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

DataKitchen

JULY 27, 2023

Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. SQL Server Integration Services (SSIS): You know it; your father used it. It does the job.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Airbnb Tech

NOVEMBER 24, 2020

During this transformation, Airbnb experienced the typical growth challenges that most companies do, including those that affect the data warehouse. In the first post of this series, we shared an overview of how we evolved our organization and technology standards to address the data quality challenges faced during hyper growth.

Data Warehouse 52

Data Warehouse Certification Data Pipeline Data 52

Monte Carlo

AUGUST 30, 2023

Often, teams run custom data tests as part of a deployment pipeline, or scheduled on production systems via job schedulers like Apache Airflow, dbt Cloud, or via in-built schedulers in your data warehouse solution. Common dbt testing use cases Time to make all these how-to instructions come to life.

SQL 52

SQL Datasets Database High Quality Data 52

Monte Carlo

APRIL 21, 2022

Adopting a cloud data warehouse like Snowflake is an important investment for any organization that wants to get the most value out of their data. Snowflake Data Quality Feature #4: Snowsight Snowsight is another Snowflake data quality feature.

Metadata 52

Metadata Bytes Government Data 52

Monte Carlo

AUGUST 10, 2023

While different solutions or tools may have significant differences in features offered, there is no real difference between data observability and data reliability engineering. Both terms are focused on the practice of ensuring healthy, high quality data across an organization. It is still relevant today.

Data Pipeline 98

Data Pipeline Software Engineer Software Engineering Machine Learning 98

Monte Carlo

MAY 25, 2023

While data orchestration tools might not be required for a pipeline to be considered “functional,” they’re nonetheless an essential component of the modern data stack, and serve as the connective tissue among various data warehouses. Ready to drive even more value from your orchestration tooling?

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

DareData

JULY 29, 2020

With these points in mind, I argue that the biggest hurdle to the widespread adoption of these advanced techniques in the healthcare industry is not intrinsic to the industry itself, or in any way related to its practitioners or patients, but simply the current lack of high-quality data pipelines.

Healthcare 52

Healthcare Data Pipeline Medical Pipeline-centric 52

Ascend.io

JUNE 8, 2023

Whether it be the marketing team seeking customer insights, the finance team working on budgeting, or executives crafting business strategies, data needs to be shared in a manner that aligns with their specific objectives and competencies. It is the stage where data truly becomes a product, delivering tangible value to its end users.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52