Monte Carlo

FEBRUARY 12, 2024

Today, this first-party data mostly lives in two types of data repositories. If it is structured data then it’s often stored in a table within a modern database, data warehouse or lakehouse. If it’s unstructured data, then it’s often stored as a vector in a namespace within a vector database.

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Monte Carlo

JANUARY 5, 2024

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. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

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. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Data Engineering Podcast

JUNE 19, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Unstruk is the DataOps platform for your unstructured data. The options for ingesting, organizing, and curating unstructured files are complex, expensive, and bespoke.

Metadata 130

Metadata Unstructured Data MongoDB MySQL 130

Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Cloud Storage 157

Cloud Storage Data Lake Cloud Unstructured Data 157

Cloudera

SEPTEMBER 17, 2018

These trends and demands lead to stress for existing data warehouse solutions – scale, efficiency, security integrations, IT budgets, ease of access. Cloudera recently launched Cloudera Data Warehouse, a modern data warehousing solution.

Data Warehouse 53

Data Warehouse SQL Portfolio MySQL 53

Cloudera

MARCH 17, 2023

When implementing a data lakehouse, the table format is a critical piece because it acts as an abstraction layer, making it easy to access all the structured, unstructured data in the lakehouse by any engine or tool, concurrently. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

Education 62

Education Unstructured Data Data Lake Data Warehouse 62

ProjectPro

JULY 22, 2016

For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse. Data lake is gaining momentum across various organizations and everyone wants to know how to implement a data lake and why.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Snowflake

APRIL 5, 2023

Two different data modeling approaches—dimensional data modeling and Data Vault—each have their own pros and cons. Modernizing a data warehouse with Snowflake Data Cloud is a smart investment that can provide significant benefits to businesses of all sizes, today more than ever as data models become ever more complex.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

U-Next

MARCH 1, 2023

Morgan Stanley Data Engineer Interview Questions As a data engineer at Morgan Stanley, you will be responsible for creating and maintaining the infrastructure for their data warehouse. Analyzing this data often involves Machine Learning, a part of Data Science. What is a data warehouse?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Knowledge Hut

MARCH 28, 2024

Salary (Average) $135,094 per year (Source: Talent.com) Top Companies Hiring Deloitte, IBM, Capgemini Certifications Microsoft Certified: Azure Solutions Architect Expert Job Role 3: Azure Big Data Engineer The focus of Azure Big Data Engineers is developing and implementing big data solutions with the use of the Microsoft Azure platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Snowflake

MAY 9, 2024

From its start with efficient batch processing with data warehouses for descriptive analytics, and the inclusion of streaming data in real time to build recommendations, we find ourselves at the forefront of a new stage of evolution: generative AI (gen AI).

Unstructured Data 94

Unstructured Data Manufacturing Retail Data Warehouse 94

Data Engineering Podcast

JUNE 12, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Unstruk is the DataOps platform for your unstructured data. The options for ingesting, organizing, and curating unstructured files are complex, expensive, and bespoke.

Metadata 100

Metadata Unstructured Data Business Intelligence MongoDB 100

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. The main exam for the Azure data engineer path is DP 203 learning path.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Does not have the resources to implement robust data governance and management.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Does not have the resources to implement robust data governance and management.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Does not have the resources to implement robust data governance and management.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

AltexSoft

AUGUST 29, 2023

The term data lake itself is metaphorical, evoking an image of a large body of water fed by multiple streams, each bringing new data to be stored and analyzed. Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

APRIL 24, 2023

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. See our post: Data Lakes vs. Data Warehouses.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Precisely

MAY 13, 2024

Wide support for enterprise-grade sources and targets Large organizations with complex IT landscapes must have the capability to easily connect to a wide variety of data sources. Whether it’s a cloud data warehouse or a mainframe, look for vendors who have a wide range of capabilities that can adapt to your changing needs.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. What is involved in integrating Manta with an organization’s data systems?

IT 100

IT Metadata MongoDB MySQL 100

Cloudera

SEPTEMBER 17, 2020

To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle. This platform, including an ad-hoc capable data warehouse service with built-in, easy-to-use visualization, made it easy for anyone to jump in and start experimenting.

Unstructured Data 81

Unstructured Data Data Warehouse Pharmaceutical MySQL 81

Knowledge Hut

JANUARY 18, 2024

Roles and Responsibilities Finding data sources and automating the data collection process Discovering patterns and trends by analyzing information Performing data pre-processing on both structured and unstructured data Creating predictive models and machine-learning algorithms Average Salary: USD 81,361 (1-3 years) / INR 10,00,000 per annum 3.

Data Science 98

Data Science Business Analyst ETL Method Data Architect 98

Monte Carlo

NOVEMBER 9, 2023

We *know* what we’re putting in (raw, often unstructured data) and we *know* what we’re getting out, but we don’t know how it got there. All of these currently exist in databases and data warehouses. Put simply, the underlying infrastructure to scale, secure, and operate LLM applications is not there yet.

Unstructured Data 86

Unstructured Data Database Data Pipeline Architecture 86

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

NOVEMBER 28, 2023

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Big resources still manage file data hierarchically using Hadoop's open-source ecosystem.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Cloud Academy

NOVEMBER 6, 2022

A Headless BI tool is a set of components that acts as middleware between your data warehouse and your business intelligence applications. It provides us with four main data-related components without the need of designing and implementing custom solutions. We work with structured , semi-structured , and unstructured data.

Cloud 52

Cloud BI Data Warehouse Business Intelligence 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. FAQs What’s the difference between a data lake and a data warehouse?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Rockset

JULY 29, 2022

Enterprise data warehouses (EDWs) became necessary in the 1980s when organizations shifted from using data for operational decisions to using data to fuel critical business decisions. Data warehouses are popular because they help break down data silos and ensure data consistency.

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 52

Knowledge Hut

APRIL 23, 2024

Below are some of the differences between Traditional Databases vs big data: Parameters Big Data Traditional Data Flexibility Big data is more flexible and can include both structured and unstructured data. Traditional Data is based on a static schema that can only work well with structured data.

Big Data 52

Big Data Relational Database Data Datasets 52

Towards Data Science

MAY 3, 2023

VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. You can use VDK to build data lakes and ingest raw data extracted from different sources, including structured, semi-structured, and unstructured data.

Data Lake 87

Data Lake Data SQL Data Warehouse 87

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

NOVEMBER 27, 2023

This is typically proprietary data – whether it is user ids, transaction history, shipping times or unstructured data from internal documents, images and videos. These are typically held in a data warehouse/lakehouse.

Unstructured Data 59

Unstructured Data Data Pipeline Data Banking 59

Knowledge Hut

MAY 31, 2023

Business Intelligence is closely knitted to the field of data science since it leverages information acquired through large data sets to deliver insightful reports. Companies utilize different approaches to deal with data in order to extract information from structured, semi-structured, or unstructured data sets.

Business Intelligence 52

Business Intelligence BI Business Analyst Consulting 52

Knowledge Hut

JUNE 23, 2023

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. What is the difference between a data engineer and a data scientist? What’s the Demand for Data Engineers? What is COSHH?

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Big Query Google’s cloud data warehouse. Data Visualization Graphic representation of a set or sets of data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40