Knowledge Hut

MAY 1, 2024

This kind of data is also known as 'big data' , given their specific characteristics in terms of volume, type of data and speed at which the data gets generated. These steps will help understand the data, extract hidden patterns and put forward insights about the data.

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Algorithm Raw Data Computer Science Data Science 98

Monte Carlo

AUGUST 30, 2023

dbt (data build tool) is a SQL-based command-line tool that offers native testing features. But there’s a lot to understand in order to both create the most value from your dbt tests and avoid leaning too heavily on a time-intensive process. Once the models are created and data transformed, `dbt test` should be executed.

SQL 52

SQL Datasets Database High Quality Data 52

DoorDash Engineering

APRIL 12, 2023

The Metrics Layer, also known as a Semantic Layer, is a critical component of the modern data stack that has recently received significant industry attention offers a powerful solution to the challenge of standardizing metric definitions. We will also dive deep into our design and implementation processes and the lessons we learnt.

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SQL Metadata Raw Data Government 82

Ascend.io

JANUARY 2, 2024

In this article, we explore how to build a data pipeline from the ground up in six steps. Recognizing the complexities inherent in this process, we also introduce a framework designed to simplify and streamline the entire pipeline construction process, boosting efficiency and scalability along the way.

Data Pipeline 52

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RandomTrees

FEBRUARY 6, 2024

Modernization in Data Engineering with GenAI Generation: The Art of Data Creation: Generative AI has emerged as a potent tool for creating synthetic datasets. Generative AI corrects data imbalances, ensuring fair sentiment analysis on e-commerce platforms, enriches training data for natural language processing (NLP) tasks.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

JANUARY 30, 2024

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

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ProjectPro

NOVEMBER 30, 2021

If you are into Data Science or Big Data, you must be familiar with an ETL pipeline. This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. How do we transform this data to get valuable insights from it?

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Knowledge Hut

DECEMBER 22, 2023

They can categorize and cluster raw data using algorithms, spot hidden patterns and connections in it, and continually learn and improve over time. Hadoop Gigabytes to petabytes of data may be stored and processed effectively using the open-source framework known as Apache Hadoop. Non-Technical Data Science Skills 1.

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Cloud Academy

JANUARY 27, 2022

Data engineering is the process of designing and implementing solutions to collect, store, and analyze large amounts of data. This process is generally called “Extract, Transfer, Load” or ETL. The format of the data will be different depending on the intended audience.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Meltano

OCTOBER 5, 2022

Data is becoming the world’s most valuable resource, according to an article in The Economist dating back to 2017. Since then, the way we compile, process, and store data has evolved significantly, and it continues to do so at incredible speed. The goal of DataOps is to speed up the process of deriving value from data.

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Knowledge Hut

JUNE 30, 2023

This article suggests the top eight data engineer books ranging from beginner-friendly manuals to in-depth technical references. What is Data Engineering? It refers to a series of operations to convert raw data into a format suitable for analysis, reporting, and machine learning which you can learn from data engineer books.

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Data Engineering Data Engineer Engineering Data Warehouse 52

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. This is one of the major reasons behind the popularity of data science. What is the role of a Data Engineer?

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Ascend.io

DECEMBER 14, 2022

How ETL Became Outdated The ETL process (extract, transform, and load) is a data consolidation technique in which data is extracted from one source, transformed, and then loaded into a target destination. In the 1980s, companies started to amass big amounts of transactional data. This causes two issues.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

RandomTrees

DECEMBER 20, 2023

The Next GEN Edge AI Application provides an immersive, intuitive and fun learning experience while saving time and money with multiple programs like Ranking, Classification and Designing. Enhanced data security. Local processing reduces the risk of sensitive data being intercepted in transit or stored in the cloud.

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IT Hospitality Healthcare Deep Learning 52

Pinterest Engineering

JULY 18, 2023

In this post, we will cover the background of time series at Pinterest, the goals of designing an expressive time series language, and some examples of how we are using this language today. Here are the features of TScript that help meet the design goals: Variables as Input Metrics from the database are referred to with variables in TScript.

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Database Software Engineer Software Engineering Raw Data 75

Knowledge Hut

JUNE 28, 2023

The answer lies in the strategic utilization of business intelligence for data mining (BI). Although these terms are sometimes used interchangeably, they carry distinct meanings and play different roles in this process. Process of analyzing, collecting, and presenting data to support decision-making.

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Data Mining Business Intelligence BI Datasets 52

Knowledge Hut

JUNE 28, 2023

Experience the power of Business Intelligence, a tech-driven methodology to gather, analyze, and present business data. This process helps showcase data in a user-friendly way with the help of reports, charts, or graphs. So, the first and foremost thing to do is to gather raw data.

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Business Intelligence BI Raw Data Education 52

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. We find it helpful to think of data operations as a factory. Imagine if a car company asked the engineers who designed cars to also build them. That’s the state of data analytics today. . The Data Journey.

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Engineering Raw Data SQL Data Engineering 60

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. They develop self-running software.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Monte Carlo

AUGUST 31, 2023

Why we originally built features with SQL Feature engineering and construction isn’t much different than other modern data pipeline architectures. You start with raw data from a source, combine it with other data, and then transform it into the desired state for your machine learning model to consume.

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SQL Data Science Machine Learning Algorithm 64

Cloudera

SEPTEMBER 15, 2022

The gathering in 2022 marked the sixteenth year for top data and analytics professionals to come to the MIT campus to explore current and future trends. A key area of focus for the symposium this year was the design and deployment of modern data platforms. What is a data fabric?

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Data Lake Analytics Application Cloud Storage Architecture 81

The Modern Data Company

MARCH 1, 2024

For today’s Chief Data Officers (CDOs) and data teams, the struggle is real. We’re drowning in data yet thirsting for actionable insights. We need a new approach, a paradigm shift that delivers data with the agility and efficiency of a speedboat – enter Data Products.

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ProjectPro

JUNE 9, 2021

As we proceed further into the blog, you will find some statistics on data engineering vs. data science jobs and data engineering vs. data science salary, along with an in-depth comparison between the two roles- data engineer vs. data scientist. vs. What does a Data Engineer do?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Ascend.io

DECEMBER 11, 2023

What Is Data Orchestration? Data orchestration is the process of efficiently coordinating the movement and processing of data across multiple, disparate systems and services within a company. The goal is to minimize manual intervention and maximize the efficiency of data use.

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AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

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Knowledge Hut

SEPTEMBER 27, 2023

Parameters Microsoft Power BI Salesforce Basics purpose Developing reports, dashboard and business intelligence tool which takes data from sources and presents it as an information to the viewer. Customer relationship management (CRM) software which is used to manage, storing and generating leads for the user in the business process.

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BI Datasets Data Security Data Analysis 52

Precisely

FEBRUARY 6, 2023

If digital transformation initiatives are to deliver on their promises, they need accurate, consistent, contextualized, and rich data. What Is Data Integrity? Until recently, the business community has lacked a clear and consistent definition of data integrity. There is no one-size-fits-all approach.

Data Integration 52

Data Integration Data Governance Government Raw Data 52

Towards Data Science

MARCH 9, 2023

Code implementations for ML pipelines: from raw data to predictions Photo by Rodion Kutsaiev on Unsplash Real-life machine learning involves a series of tasks to prepare the data before the magic predictions take place. And that’s it.

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Machine Learning Building Datasets Scala 75

AltexSoft

JUNE 26, 2023

Data collection as the first step in the decision-making process, driven by machine learning. In machine learning projects, data collection precedes such stages as data cleaning and preprocessing, model training and testing, and making decisions based on a model’s output. Data engineering explained in 14 minutes.

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Knowledge Hut

FEBRUARY 2, 2024

Website Development is highly sought after, and great website designers tend to get paid in lakhs for a single project. What’s more, if you’re more of a set-your-own-hours kind of person, certified website developers can most definitely pursue freelancing or even create their own Web Development Agency!

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Programming Language Amazon Web Services Cloud Computing Java 98

Data Engineering Weekly

JANUARY 15, 2023

SiliconANGLE theCUBE: Analyst Predictions 2023 - The Future of Data Management By far one of the best analyses of trends in Data Management. The author writes an exciting article about switching to Github actions for dbt to save $65,000 [link] Sponsored: Upsolver - Write a SQL Query, Get a Data-in-Motion Pipeline!

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Ascend.io

SEPTEMBER 14, 2023

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. Typing Dynamically typed, but can use type hints.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

dbt Developer Hub

APRIL 19, 2023

This tutorial aims to solve this by providing the definitive guide to dimensional modeling with dbt. The goal of dimensional modeling is to take raw data and transform it into Fact and Dimension tables that represent the business. This helps ensure that the modeled data is easily usable.

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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. Why Use AWS Glue?

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Knowledge Hut

DECEMBER 29, 2023

They are not only responsible for developing the UI, but they also ensure a balance between design and functionality and ensure speed and scalability. To get an in-depth knowledge of web development, enroll in Web Design course fees to check out the details. These frameworks would speed up the development process for you.

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Portfolio Amazon Web Services Programming Language Coding 98

AltexSoft

MAY 12, 2023

By understanding these aspects comprehensively, you can harness the true potential of unstructured data and transform it into a strategic asset. What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization.

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DareData

JULY 29, 2020

Odds are that your local hospital, pharmacy or medical institution's definition of being data-driven is keeping files in labelled file cabinets, as opposed to one single drawer. What makes a good Data Pipeline? A simple example of a data pipeline, transforming raw data, and converting it into a dashboard.

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