Knowledge Hut

FEBRUARY 16, 2023

Demand for data engineers is at a peak today globally due to the massive amount of data that companies accumulate and work with this data to draw actionable insights and make better business decisions. To do that, the generated data must be interpreted to be understood by the end user. What Does a Data Engineer Do?

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Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Data Visualization Graphic representation of a set or sets of data.

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Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineer is one of the most popular job profiles in the data industry. This blog on Big Data Engineer salary gives you a clear picture of the salary range according to skills, countries, industries, job titles, etc. Big Data gets over 1.2 What does a big data engineer do?

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Towards Data Science

JANUARY 16, 2024

My personal take on justifying the existence of Data Mesh A senior stakeholder at one my projects mentioned that they wanted to decentralise their data platform architecture and democratise data across the organisation. When I heard the words ‘decentralised data architecture’, I was left utterly confused at first!

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Data Warehouse Data Architecture Relational Database NoSQL 64

Towards Data Science

JUNE 8, 2023

Some organizations will attempt to diffuse the responsibility widely across data stewards, data owners, data engineering and governance committees, each owning a fraction of the data value chain. Why is data quality ownership important? The whole needs to be greater than the sum of its parts.

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Data Governance Government Generalist Data Engineering 75

Knowledge Hut

NOVEMBER 28, 2023

Data Science is a field where job offers have grown exponentially in the last few years alone. People use programming mathematics, statistics, and other domain knowledge in data science to extract important insights from big data. You can check out a Data Science Bootcamp to learn more about the field.

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Knowledge Hut

NOVEMBER 28, 2023

As a result, most companies are transforming into data-driven organizations harnessing the power of big data. Here Data Science becomes relevant as it deals with converting unstructured and messy data into structured data sets for actionable business insights. Who is a Data Architect?

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Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

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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? What is Data Science?

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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.

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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.

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Data Pipeline Architecture Kafka AWS 52

ProjectPro

JANUARY 24, 2023

It is a popular ETL tool well-suited for big data environments and extensively used by data engineers today to build and maintain data pipelines with minimal effort. You can leverage AWS Glue to discover, transform, and prepare your data for analytics. PREVIOUS NEXT <

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ProjectPro

FEBRUARY 16, 2023

Focus Historical data analysis, reporting, and visualization. Predictive and prescriptive analytics, machine learning, and deep learning. Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems. Individual data analysis takes a long time. PREVIOUS NEXT <

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Knowledge Hut

OCTOBER 5, 2023

An AWS Big Data Specialist is an IT professional who efficiently designs, analyzes, and maintains data, has experience AWS analytics services, and has cleared the AWS Big Data Specialty certification exam. Experience The more years you invest as a Big Data Specialist, the higher your salary package will be.

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Big Data AWS Certification Amazon Web Services 52

Towards Data Science

JANUARY 17, 2024

These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction. They are designed to handle the challenges of big data like size, speed, and structure. Data engineers often face a plethora of choices. Open a new Jupyter notebook to begin.

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Monte Carlo

SEPTEMBER 6, 2022

Our biggest priority at Monte Carlo is to make the lives of our customers easier by reducing data downtime and helping them accelerate the adoption of reliable data at their companies. These features combine the best of both data lakes and data warehouses into a new type of data store: the data lakehouse.

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ProjectPro

FEBRUARY 16, 2023

ETL is a critical component of success for most data engineering teams, and with teams harnessing it with the power of AWS, the stakes are higher than ever. Data Engineers and Data Scientists require efficient methods for managing large databases, which is why centralized data warehouses are in high demand.

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Monte Carlo

AUGUST 31, 2023

And finally, we’ll take a closer look at how best-in-class teams can achieve high data quality at each stage of the data pipeline and what it takes to maintain data trust at scale. What is Data Quality? In our opinion, data quality frequently gets a bad rep.

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Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Define data architecture standards and best practices.

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BI Business Intelligence Data Cleanse Business Analyst 52

Monte Carlo

MARCH 14, 2023

Enter BlaBlaCar, which has made real progress on tough challenges like self service analytics and data mesh over the past few years, leading to a reduction in data incidents and time to insights. We had some new use cases around data science that were hard to fit into our existing org. Here’s their story.

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Transportation Government Google Cloud Architecture 40

Knowledge Hut

DECEMBER 29, 2023

Data Engineering is the most demanding and fruitful career option, as most companies rely on their data to make significant growth decisions. First, they gather all the data from different resources and segregate it into fruitful data sets. The highlight feature of this data engineer toolkit is spark streaming.

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Data Engineering Data Engineer Engineering BI 40

ProjectPro

JANUARY 19, 2022

Planning to land a successful job as an Azure Data Engineer? Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer.

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Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

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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.

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Knowledge Hut

JANUARY 18, 2024

I’ve often noticed that people use terms like Data Science and Artificial Intelligence ( AI ) interchangeably. The key connection between Data Science and AI is data. Understanding  Data Science course eligibility  can help you understand more about Data Science. What is Data Science?

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AltexSoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

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Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

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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.

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Data Engineering Data Engineer Engineering Hadoop 40

U-Next

AUGUST 11, 2022

A Data Scientist’s job entails deciphering and analyzing complex, unstructured data gathered from several sources. Read on to learn about the career opportunities and salary of a Data Scientist. Data Science project workflows include several steps. Skill requirements for Data Science.

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Data Science Data Cleanse Unstructured Data Machine Learning 40

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

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Data Lake Data Warehouse Unstructured Data Raw Data 52

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

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AltexSoft

JULY 18, 2023

Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks.

Big Data 52

Big Data Data Process Process Hadoop 52

Monte Carlo

JUNE 14, 2023

For example, data may be extracted from multiple sources, reorganized, and joined at different times before ultimately being served to its final destination. Why is data pipeline architecture important? Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

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ProjectPro

JANUARY 31, 2022

Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse? Snowflake Features that Make Data Science Easier Building Data Applications with Snowflake Data Warehouse Snowflake Data Warehouse Architecture How Does Snowflake Store Data Internally? What Does Snowflake Do?

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Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 22, 2021

According to the Businesswire report , the worldwide big data as a service market is estimated to grow at a CAGR of 36.9% This clearly indicates that the need for Big Data Engineers and Specialists would surge in the future years. PySpark Interview Questions for Data Engineer Q1. from 2019 to 2026, reaching $61.42

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ProjectPro

JANUARY 24, 2023

The three essential functions of combining Google Analytics and BigQuery include- 1) Data Manipulation BigQuery allows for data manipulation and transformation, such as filtering, joins, and aggregations, which helps to prepare the data for analysis and visualization. The equality operators equal (=), not equal (!=

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ProjectPro

JANUARY 31, 2023

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. Get ready to expand your knowledge and take your big data career to the next level! “Data analytics is the future, and the future is NOW!

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