Monte Carlo

JULY 25, 2023

What is data curation? Data curation is the process of transforming and enriching larger amounts of raw data into smaller, more widely accessible subsets of data that provide additional value to the organization or the intended use case. It would also make the data engineering team a bottleneck.

Raw Data 52

Raw Data Data Warehouse Data Architecture 52

Data Engineering Podcast

DECEMBER 16, 2019

The solution to discoverability and tracking of data lineage is to incorporate a metadata repository into your data platform. The metadata repository serves as a data catalog and a means of reporting on the health and status of your datasets when it is properly integrated into the rest of your tools.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

Monte Carlo

AUGUST 25, 2023

One advantage of data warehouses is their integrated nature. As fully managed solutions, data warehouses are designed to offer ease of construction and operation. A warehouse can be a one-stop solution, where metadata, storage, and compute components come from the same place and are under the orchestration of a single vendor.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Precisely

OCTOBER 5, 2023

According to the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, 77% of data and analytics professionals say data-driven decision-making is the top goal of their data programs. That’s where data enrichment comes in.

Raw Data 69

Raw Data Insurance Datasets Telecommunication 69

DataKitchen

FEBRUARY 2, 2023

DataOps Automation (Orchestration, Environment Management, Deployment Automation) DataOps Observability (Monitoring, Test Automation) Data Governance (Catalogs, Lineage, Stewardship) Data Privacy (Access and Compliance) Data Team Management (Projects, Tickets, Documentation, Value Stream Management) What are the drivers of this consolidation?

Metadata 52

Metadata BI Government Data Science 52

AltexSoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Striim

AUGUST 7, 2024

Transform Raw Data into AI-generated Actions and Insights in Seconds In today’s fast-paced business environment, the ability to quickly transform raw data into actionable insights is crucial. Let’s dial in on some of the specific goals your organization can accomplish thanks to leveraging Striim and Snowflake.

IT 52

IT Entertainment MySQL Raw Data 52

dbt Developer Hub

NOVEMBER 28, 2021

This could just as easily have been Snowflake or Redshift, but I chose BigQuery because one of my data sources is already there as a public dataset. dbt seeds data from offline sources and performs necessary transformations on data after it's been loaded into BigQuery. Let's dig into each data source one at a time.

Raw Data 52

Raw Data Metadata Database Datasets 52

Monte Carlo

JUNE 28, 2022

Over the past several years, cloud data lakes like Databricks have gotten so powerful (and popular) that according to Mordor Intelligence , the data lake market is expected to grow from $3.74 Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Rockset

MAY 8, 2023

Vector search is a method for efficiently finding and retrieving similar items from a large dataset based on representations of the data in a high-dimensional space. In this context, items can be anything, such as documents, images, or sounds, and are represented as vector embeddings. The workflow for vector search at Spotify.

Metadata 52

Metadata Algorithm Datasets Google Cloud 52

dbt Developer Hub

DECEMBER 5, 2021

We’ve also included some sample raw data to add to your warehouse so you can run these projects yourself! At this stage, the README and dbt_project.yml are just artifacts from the dbt init command , and don’t yet have specific documentation or configuration. Caveats and Assumptions ​ This is an art, not science!

Project 52

Project Building Metadata BI 52

Hepta Analytics

FEBRUARY 14, 2022

When the business intelligence needs change, they can go query the raw data again. ELT: source Data Lake vs Data Warehouse Data lake stores raw data. The purpose of the data is not determined. The data is easily accessible and is easy to update. x+ and set minimum memory to 5GB.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 29, 2023

DOCTYPE html> is a declaration that should be added at the start of every HTML document to indicate to the browser what type of document to expect, i.e. HTML. The “head” tags (<head> and </head>) contain the metadata or information about the website.

Portfolio 98

Portfolio Amazon Web Services Programming Language Coding 98

Workfall

AUGUST 14, 2023

DBT, which stands for Data Build Tool, is a powerful tool designed to transform and manage data in a scalable and reproducible manner. It allows data engineers to define and execute data transformations in a structured and modular way. Initialize the Airflow metadata database by running airflow initdb in your terminal.

Data Pipeline 62

Data Pipeline Data Raw Data Database 62

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more. How systems exchange data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Ascend.io

DECEMBER 11, 2023

Data orchestration is the process of efficiently coordinating the movement and processing of data across multiple, disparate systems and services within a company. In comparison, general data orchestration does not offer this degree of contextual insight Why Data Orchestration Is Important (But an Unnecessary Complication?)

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

Databand.ai

JULY 28, 2022

Those tasks are saving the extracted data in the data lake (or warehouse or lakehouse). Other tasks, probably SQL jobs orchestrated with DBT, are running transformation on the loaded data. They are querying raw data tables, enriching them, joining between tables, and creating business data – all ready to be used.

Metadata 52

Metadata Data Lake Datasets Data Warehouse 52

AltexSoft

DECEMBER 23, 2022

For example, Online Analytical Processing (OLAP) systems only allow relational data structures so the data has to be reshaped into the SQL-readable format beforehand. In ELT, raw data is loaded into the destination, and then it receives transformations when it’s needed. ELT allows them to work with the data directly.

Process 52

Process Building Raw Data Data Lake 52

Monte Carlo

APRIL 1, 2021

Data Catalogs Can Drown in a Data Lake Although exceptionally flexible and scalable, data lakes lack the organization necessary to facilitate proper metadata management and data governance. Data discovery tools and platforms can help. Image courtesy of Adrian on Unsplash.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Architecture overview. Separate storage.

IT 92

IT Data Lake Data Warehouse Cloud Storage 92

ProjectPro

FEBRUARY 25, 2022

Each stage of the data pipeline passes processed data to the next step, i.e., it gives the output of one phase as input data into the next phase. Data Preprocessing- This step entails collecting raw and inconsistent data selected by a team of experts.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

ProjectPro

SEPTEMBER 16, 2021

Code Repository : The data and code repository has to be selected such that it fits into the MLOps stack being used, especially if it is on the cloud ML Pipeline : Similar to data pipelines, ML pipelines help carry the state of the machine learning project from data to ML output. Markdown files, particularly readme.md

Project 52

Project Amazon Web Services Machine Learning Data Science 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Airbnb Tech

JUNE 1, 2021

When a metric is defined in Minerva, authors are required to provide important self-describing metadata. Prior to Minerva, all such metadata often existed only as undocumented institutional knowledge or in chart definitions scattered across various business intelligence tools.

Datasets 52

Datasets Pipeline-centric Metadata Data Science 52

ProjectPro

AUGUST 11, 2021

The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. The RDBMS can either be directly accessed from the data warehouse layer or stored in data marts designed for specific enterprise departments.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

JUNE 14, 2023

Data transformation dbt – Short for data build tool, is the open source leader for transforming data once it’s loaded into your warehouse. Dataform – Now part of the Google Cloud , Dataform allows you to transform raw data from your warehouse into something usable by BI and analytics tools.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Data Engineering Podcast

JANUARY 28, 2018

How does Dat manage conflict resolution and data versioning when replicating between multiple machines? One of the primary use cases that is mentioned in the documentation and website for Dat is that of hosting and distributing open data sets, with a focus on researchers. And it can send a link for that. Sloan Foundation.

Data 100

Data Project Data Management Electronics 100

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. Engage with different teams like data science tean=ms, etc.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

AUGUST 21, 2015

Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. Data that can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi-structured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

AltexSoft

MAY 12, 2023

Unlike structured data, which is organized into neat rows and columns within a database, unstructured data is an unsorted and vast information collection. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc. Some examples of unstructured data Text documents.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

RandomTrees

FEBRUARY 6, 2024

Generative AI corrects data imbalances, ensuring fair sentiment analysis on e-commerce platforms, enriches training data for natural language processing (NLP) tasks. Ingestion: The Art of Data Assimilation: Ensuring the digital document accurately reflects the original handwritten material.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Monte Carlo

MARCH 28, 2023

Zero-ETL What it is : A misnomer for one thing; the data pipeline still exists. Today, data is often generated by a service and written into a transactional database. An automatic pipeline is deployed which not only moves the raw data to the analytical data warehouse, but modifies it slightly along the way.

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

Monte Carlo

MAY 19, 2022

From the start, the data steward role was heavily intertwined with data governance and metadata management. However, stewards also took on leadership across initiatives designed to tame the “5 v’s” of big data: volume, value, variety, velocity, and veracity.

Generalist 52

Generalist Data Governance Government Metadata 52

Towards Data Science

APRIL 3, 2023

Zero-ETL What it is : A misnomer for one thing; the data pipeline still exists. Today, data is often generated by a service and written into a transactional database. An automatic pipeline is deployed which not only moves the raw data to the analytical data warehouse, but modifies it slightly along the way.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Monte Carlo

JANUARY 4, 2024

With an enormous amount of data produced and consumed across the organization, Whatnot’s data teams needed to introduce a process to help everyone get and stay on the same page — even as the platform continued to evolve and grow. Enter data contracts. That schema is then pushed through the common interface. “One

Data 40

Data Metadata Software Engineer Software Engineering 40

Monte Carlo

AUGUST 19, 2023

Data Transformation and Modeling Data transformation and modeling are often used interchangeably, but they are two very different processes. When you transform your data, you are taking raw data and cleaning it up with business logic to get the data ready for analysis and reporting.

Building 52

Building BI Data Lake Data Governance 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64