Ascend.io

AUGUST 31, 2023

For example, unlike traditional platforms with set schemas, data lakes adapt to frequently changing data structures at points where the data is loaded , accessed, and used. These fluid conditions require unstructured data environments that natively operate with constantly changing formats, data structures, and data semantics.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

ProjectPro

FEBRUARY 16, 2023

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

Towards Data Science

MAY 3, 2023

Data Engineering Learn about slow change dimensions (SCD) and how to implement SCD Type 2 in VDK Photo by Joshua Sortino on Unsplash Data is the backbone of any organization, and in today’s fast-paced world, it is crucial to keep track of its versions.

Data Lake 85

Data Lake SQL Data Data Warehouse 85

DareData

JULY 5, 2023

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. ETL is the acronym for Extract, Transform, and Load.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 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. Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Snowflake

APRIL 5, 2023

With Snowflake’s support for multiple data models such as dimensional data modeling and Data Vault, as well as support for a variety of data types including semi-structured and unstructured data, organizations can accommodate a variety of sources to support their different business use cases.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

The Modern Data Company

MAY 10, 2023

Data lakes provide the flexibility you need because they can store structured, unstructured, and semi-structured data in their native formats. Wants to leverage the power of advanced analytics, AI, and machine learning on large volumes of raw data. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Data lakes provide the flexibility you need because they can store structured, unstructured, and semi-structured data in their native formats. Wants to leverage the power of advanced analytics, AI, and machine learning on large volumes of raw data. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Data lakes provide the flexibility you need because they can store structured, unstructured, and semi-structured data in their native formats. Wants to leverage the power of advanced analytics, AI, and machine learning on large volumes of raw data. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Knowledge Hut

DECEMBER 22, 2023

Power BI is a technology-driven business intelligence tool or an array of software services, apps, and connectors to convert unrelated and raw data into visually immersive, coherent, actionable, and interactive insights and information. Microsoft developed it and combines business analytics, data visualization, and best practices.

BI 98

BI Business Intelligence Machine Learning SQL 98

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is Data Science? What are the roles and responsibilities of a Data Engineer? And many more. And many more.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

JULY 4, 2023

Among the highest-paying roles in this field are Data Architects, Data Scientists, Database Administrators, and Data Engineers. A Data Architect can earn up to 1,30,000, while a Data Scientist can expect a salary range of $90,000-$1,30,000 per year. Build data systems and pipelines.

Data Analytics 52

Data Analytics Data Architect Transportation Data Science 52

Monte Carlo

JUNE 28, 2022

Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem. By design, data was less structured with limited metadata and no ACID properties. “I’m excited to leverage Monte Carlo’s data observability for our Databricks environment.”

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Monte Carlo

AUGUST 31, 2023

In many ways, the cloud makes data easier to manage, more accessible to a wider variety of users, and far faster to process. Not long after data warehouses moved to the cloud, so too did data lakes (a place to transform and store unstructured data), giving data teams even greater flexibility when it comes to managing their data assets.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

DECEMBER 29, 2023

There are many data science fields in which experts may contribute to the success of a business, and you can hone the abilities you need by specializing in data science subfields. Data Engineering and Warehousing The data is the lifeblood of every successful Data Science endeavor.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

OCTOBER 15, 2014

Just before we jump on to a detailed discussion on the key components of the Hadoop Ecosystem and try to understand the differences between them let us have an understanding on what is Hadoop and what is Big Data. What is Big Data and Hadoop? Their data engineers use Pig for data processing on their Hadoop clusters.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Meltano

OCTOBER 5, 2022

Interested in becoming a data engineer? The need for data experts in the U.S. job market is expected to grow by 22% in this decade, and according to LinkedIn’s 2020 report , a data engineer is listed as the 8th fastest growing job today. But what is data engineering exactly and what does a data engineer do?

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 52

ProjectPro

SEPTEMBER 26, 2021

According to a survey, big data engineering job interviews increased by 40% in 2020 compared to only a 10% rise in Data science job interviews. Table of Contents Big Data Engineer - The Market Demand Who is a Big Data Engineer? Most of these are performed by Data Engineers.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Rockset

NOVEMBER 1, 2018

Over a decade after the inception of the Hadoop project, the amount of unstructured data available to modern applications continues to increase. This longevity is a testament to the community of analysts and data practitioners who are familiar with SQL as well as the mature ecosystem of tools around the language.

Raw Data 40

Raw Data SQL Unstructured Data NoSQL 40

Monte Carlo

AUGUST 25, 2023

With pre-built functionalities and robust SQL support, data warehouses are tailor-made to enable swift, actionable querying for data analytics teams working primarily with structured data. Commonly, you’ll find data formats such as JSON, Apache Parquet, and Apache Avro in these environments. Or maybe both.)

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

ProjectPro

OCTOBER 18, 2021

To build such ML projects, you must know different approaches to cleaning raw data. From the outset of machine learning, it was challenging to work with unstructured data (image dataset) and transform it into structured data (texts). Build an Awesome Job Winning Data Engineering Projects Portfoli o 9.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

ProjectPro

NOVEMBER 14, 2015

From Data Engineering Fundamentals to full hands-on example projects , check out data engineering projects by ProjectPro 2. Data Integration Businesses seldom start big. Streaming analytics is a real-time analysis of data streams that must (almost instantaneously) report abnormalities and trigger suitable actions.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

MAY 20, 2015

Several big data companies are looking to tame the zettabyte’s of BIG big data with analytics solutions that will help their customers turn it all in meaningful insights. Big data engineers at Palantir are driven by the mission of empowering enterprises to make sense of their data to solve the most persistent problems.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Rockset

DECEMBER 9, 2019

As a data engineer, my time is spent either moving data from one place to another, or preparing it for exposure to either reporting tools or front end users. As data collection and usage have become more sophisticated, the sources of data have become a lot more varied and disparate, volumes have grown and velocity has increased.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Scalability.

Process 52

Process Building Raw Data Data Lake 52

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. Data engineering explained in 14 minutes.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Ascend.io

DECEMBER 14, 2022

As data became the backbone of most businesses, data integration emerged as one of the most significant challenges. Today, a good part of the job of a data engineer is to move data from one place to another by creating pipelines that can be either ETL vs. ELT. This causes two issues. This is when ELT came in.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

Data Engineering Weekly

MAY 8, 2023

Receipt table (later referred to as table_receipts_index): It turns out that all the receipts were manually entered into the system, which creates unstructured data that is error-prone. This data collection method was chosen because it was simple to deploy, with each employee responsible for their own receipts.

Process 52

Process Banking Raw Data Finance 52

Monte Carlo

FEBRUARY 15, 2023

Cleaning Bad data can derail an entire company, and the foundation of bad data is unclean data. Therefore it’s of immense importance that the data that enters a data warehouse needs to be cleaned. Data can be loaded in batches or can be streamed in near real-time. They need to be transformed.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Towards Data Science

FEBRUARY 9, 2024

Viewing Data Lakes as a strategy rather than a product emphasizes their role as a staging area for structured and unstructured data, potentially interacting with Data Warehouses. Amid the rush to keep up with generative AI and Large Language Model trends, specialized data stores like vector databases become essential.

Building 81

Building Transportation Data Lake Metadata 81

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse? Enter Snowpark

Engineering 83

Engineering Raw Data Data Science Scala 83

Databand.ai

JULY 19, 2023

The Transform Phase During this phase, the data is prepared for analysis. This preparation can involve various operations such as cleaning, filtering, aggregating, and summarizing the data. The goal of the transformation is to convert the raw data into a format that’s easy to analyze and interpret.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

ProjectPro

FEBRUARY 8, 2023

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses.

AWS 98

AWS Scala Metadata Data Lake 98