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. Lack of governance Our platform lacked governance policies for metric definitions.

SQL 82

SQL Metadata Raw Data Government 82

Knowledge Hut

DECEMBER 22, 2023

Data science uses machine learning algorithms like Random Forests, K-nearest Neighbors, Naive Bayes, Regression Models, etc. They can categorize and cluster raw data using algorithms, spot hidden patterns and connections in it, and continually learn and improve over time. Packages and Software OpenCV.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Snowflake

APRIL 7, 2023

It transforms multiple financial and operational systems’ raw data into a common, friendly data model that people can understand. With Maxa, business teams go from manually managing core systems of record data to working with a single system of insights. Maxa Maxa automates financial and ERP insights.

Raw Data 108

Raw Data Portfolio Building SQL 108

Monte Carlo

MARCH 28, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

Knowledge Hut

APRIL 25, 2024

You'll be better able to comprehend the complex ideas in this field if you have a solid understanding of the characteristics of big data in data analytics and a list of essential features for new data platforms. What Are the Different Features of Big Data Analytics? The three most typical categories 5.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Ascend.io

JANUARY 2, 2024

However, this perspective overlooks the intricacies and transformative nature inherent in data pipelines. While it’s true that a data pipeline involves moving data from one location to another, this definition is overly simplistic and doesn’t capture the essence of what sets a data pipeline apart.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Ascend.io

DECEMBER 14, 2022

But in a world that favors the here and now, ETL processes lack in the area of providing analysts with new, fresh data. Low in Visibility End-users won’t be able to access all the data in the final destination, only the data that was transformed and loaded. This causes two issues. Final Thoughts on ETL vs.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 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?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

RandomTrees

DECEMBER 20, 2023

In this way, Edge AI facilitates the storage and computation of data, making it more accessible for users. Moreover, Edge AI combines AI algorithms with edge computing capabilities on local devices. Thus, data can get processed and analyzed without requiring connectivity and integration, allowing users to access data from various sources.

IT 52

IT Hospitality Healthcare Deep Learning 52

Monte Carlo

OCTOBER 2, 2023

Copenhagen-based Abacus Medicine is working to make medicine more affordable and accessible for patients while saving costs for healthcare systems. The data engineering team had little visibility into data health, and was experiencing significant problems around accessibility, flexibility, scalability and storage. “We

Pharmaceutical 72

Pharmaceutical Healthcare Machine Learning Architecture 72

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. Companies need more than definitions.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MARCH 1, 2024

Each Data Product is designed for a specific purpose, equipped with the necessary data, transformations, and metadata. Data Products simplify access and processing, empowering faster decision-making. Beyond the Analogy: A Closer Look at Data Products Think of a Data Product as a Lego brick.

Database-centric 40

Database-centric Data Lake Government Retail 40

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 Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Cloud Academy

JANUARY 27, 2022

A data engineer is an engineer who creates solutions from raw data. A data engineer develops, constructs, tests, and maintains data architectures. Let’s review some of the big picture concepts as well finer details about being a data engineer. Earlier we mentioned ETL or extract, transform, load.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Towards Data Science

APRIL 3, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

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. Companies need more than definitions.

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. Companies need more than definitions.

Data Management 52

Data Management Data Lake Management Data Warehouse 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. PREVIOUS NEXT <

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

Knowledge Hut

JUNE 28, 2023

By examining these factors, organizations can make informed decisions on which approach best suits their data analysis and decision-making needs. Parameter Data Mining Business Intelligence (BI) Definition The process of uncovering patterns, relationships, and insights from extensive datasets.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

Knowledge Hut

DECEMBER 26, 2023

The spectrum of sources from which data is collected for the study in Data Science is broad. These data have been accessible to us because of the advanced and latest technologies which are used in the collection of data. What is the role of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

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.

Data Integration 52

Data Integration Data Governance Government Raw Data 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. Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

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? What is Data Science?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. While the open-source part is definitely a good thing, it requires a high level of expertise as there’s often no GUI.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Monte Carlo

FEBRUARY 15, 2023

This article will define in simple terms what a data warehouse is, how it’s different from a database, fundamentals of how they work, and an overview of today’s most popular data warehouses. What is a data warehouse? An ETL tool or API-based batch processing/streaming is used to pump all of this data into a data warehouse.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Meltano

OCTOBER 5, 2022

DataOps uses a wide range of technologies such as machine learning, artificial intelligence, and various data management tools to streamline data processing, testing, preparing, deploying, and monitoring. This results in a system that gives organizations control over the data flow so that anomalies can be spotted automatically.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

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.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

DareData

JULY 29, 2020

The Challenges of Medical Data In recent times, there have been several developments in applications of machine learning to the medical industry. 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.

Healthcare 52

Healthcare Data Pipeline Medical Pipeline-centric 52

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.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

JANUARY 4, 2024

Over the last two years, data contracts have become one of most talked about (and hotly debated ) topics in data engineering. And like any new — and admittedly abstract — concept, there are several different definitions of data contracts floating around on LinkedIn , Medium , and Substack.

Data 40

Data Metadata Software Engineer Software Engineering 40

ProjectPro

FEBRUARY 16, 2023

If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. Your SQL skills as a data engineer are crucial for data modeling and analytics tasks.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Knowledge Hut

SEPTEMBER 27, 2023

Performing marketing operation, getting sales lead Data Integration The data source for it is generally various Microsoft SQL server, Excel, csv and Microsoft tools Here the input data is from the various ecosystem an also the interface created can integrate with multiple system. Comparatively, it is more user friendly.

BI 52

BI Datasets Data Security Data Analysis 52

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 ETL Tools 52

Grouparoo

NOVEMBER 29, 2021

Alternatively, this can be data generated by another process and then made available for subsequent processing. Therefore, the source data may be raw, unfiltered, and unrefined, or polished and fully formed. In this article, we'll look at the definition of data sources and their general types.

Raw Data 40

Raw Data Big Data Relational Database Data Warehouse 40

Ascend.io

DECEMBER 11, 2023

Is your data stuck in separate areas within your company, making it hard to use effectively? Here’s the deal: for data to truly drive your business forward, you need a reliable and scalable system to keep it moving without hiccups. In other words, you need data orchestration. Not every team needs data orchestration.

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

Netflix Tech

SEPTEMBER 10, 2019

Due to compression and high performance computing, scientists can analyze billions of rows of raw data on their laptops using languages and statistical libraries they are familiar with like Python and R. Heavily used or high value scripts were sometimes converted into Shiny apps , allowing easy access to these novel features.

Raw Data 86

Raw Data Python Datasets SQL 86