Precisely

NOVEMBER 11, 2024

This involves integrating customer data across various channels – like your CRM systems, data warehouses, and more – so that the most relevant and up-to-date information is used consistently in your customer interactions. Focus on high-quality data. Data quality is essential for personalization efforts.

High Quality Data 52

High Quality Data Data Data Warehouse Technology 52

Monte Carlo

OCTOBER 31, 2024

There are dozens of data engineering tools available on the market, so familiarity with a wide variety of these can increase your attractiveness as an AI data engineering candidate. Data Storage Solutions As we all know, data can be stored in a variety of ways.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

Monte Carlo

JANUARY 25, 2023

In this article, Chad Sanderson , Head of Product, Data Platform , at Convoy and creator of Data Quality Camp , introduces a new application of data contracts: in your data warehouse. In the last couple of posts , I’ve focused on implementing data contracts in production services.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Data Engineering Weekly

FEBRUARY 2, 2025

Shifting left involves moving data processing upstream, closer to the source, enabling broader access to high-quality data through well-defined data products and contracts, thus reducing duplication, enhancing data integrity, and bridging the gap between operational and analytical data domains.

Data Engineer 57

Data Engineer Data Engineering Engineering Data Lake 57

Hevo

SEPTEMBER 25, 2024

The importance of data quality within an organization cannot be overemphasized as it is a critical aspect of running and maintaining an efficient data warehouse. High-quality data ensures that organizations make data-driven decisions to […]

Data Warehouse 40

Data Warehouse High Quality Data Datasets Data 40

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 Engineer 130

Data Engineer Data Engineering Engineering ETL Tools 130

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

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

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 81

Data Warehouse Data Lake Government High Quality Data 81

Lyft Engineering

OCTOBER 3, 2023

High-quality data is necessary for the success of every data-driven company. It is now the norm for tech companies to have a well-developed data platform. This makes it easy for engineers to generate, transform, store, and analyze data at the petabyte scale. What and Where is Data Quality?

Big Data 87

Big Data Metadata Data Warehouse Data 87

Precisely

JULY 12, 2024

Consistent: Data is consistently represented in a standard way throughout the dataset. Quality data must meet all these criteria. If it is lacking in just one way, it could compromise any data-driven initiative. However, simply having high-quality data does not, of itself, ensure that an organization will find it useful.

Data Integration 105

Data Integration Datasets Data Data Governance 105

Data Engineering Weekly

AUGUST 25, 2024

It then passes through various ranking systems like Mustang, Superroot, and NavBoost, which refine the results to the top 10 based on factors like content quality, user behavior, and link analysis. The author writes an overview of the performance implication of disaggregated systems compared to traditional monolithic databases.

Data Engineer 70

Data Engineer Data Engineering Engineering Database-centric 70

Workfall

JULY 4, 2023

With DBT, they weave powerful SQL spells to create data models that capture the essence of their organization’s information. DBT’s superpowers include seamlessly connecting with databases and data warehouses, performing amazing transformations, and effortlessly managing dependencies to ensure high-quality data.

Data Warehouse 69

Data Warehouse SQL Database PostgreSQL 69

Data Engineering Weekly

APRIL 14, 2024

link] Intel: Four Data Cleaning Techniques to Improve Large Language Model (LLM) Performance If someone asks me to define LLM, this is my one-line definition. Large Language Models: Turning messy data into surprisingly coherent nonsense since 2023. High-quality data is the cornerstone of LLM.

Data Engineer 62

Data Engineer Data Engineering Engineering Business Intelligence 62

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

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

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

Precisely

JULY 18, 2024

A data fabric offers several key benefits that transform your data management: Accelerates analytics and decision-making processes by enhancing data accessibility through seamless data integration and retrieval across diverse environments. Increase metadata maturity.

Data Management 52

Data Management Management Metadata Database-centric 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

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

AUGUST 30, 2024

It’s our goal at Monte Carlo to provide data observability and quality across the enterprise by monitoring every system vital in the delivery of data from source to consumption. We started with popular modern data warehouses and quickly expanded our support as data lakes became data lakehouses.

SQL 40

SQL Engineering Data Lake High Quality Data 40

Wayne Yaddow

FEBRUARY 18, 2025

Carefully curated test data (realistic samples, edge cases, golden datasets) that reveal issuesearly. Proper tooling & environment (Python ecosystem for Great Expectations, data warehouse credentials and macros fordbt).

Data Pipeline 52

Data Pipeline SQL Raw Data Python 52

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

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

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

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 Data Warehouse Scala 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

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

Data Engineering Weekly

MAY 19, 2024

The article about data asset pricing is one of the comprehensive thoughts I came across about pricing models, establishing two basic factors. Data value depends on the users and the use cases Data quality is multi-dimensional, and high-quality data costs more. Register now and join us on May 22nd!

Data Engineer 52

Data Engineer Data Engineering Engineering Kafka 52

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 Engineer 52

Data Engineer Data Engineering Engineering Kafka 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 67

Raw Data Data Business Intelligence Data Engineering 67

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

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

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

Monte Carlo

AUGUST 13, 2024

Our perspective: How Gartner differentiates between traditional data quality monitoring and data observability is crucial for understanding their mandatory features. In our experience, static, event-based monitoring – SQL monitors, data testing, etc.

Data 52

Data Data Warehouse Data Pipeline Data Architecture 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 Structured Data 52