Towards Data Science

FEBRUARY 6, 2024

The disconnection between the operational teams immersed in the day-to-day functions and those extracting business value from data generated in the operational processes still remains a significant friction point. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

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Systems Raw Data Metadata Data Cleanse 76

ProjectPro

FEBRUARY 16, 2023

The demand for skilled data engineers who can build, maintain, and optimize large data infrastructures does not seem to slow down any sooner. At the heart of these data engineering skills lies SQL that helps data engineers manage and manipulate large amounts of data. use SQL, compared to 61.7%

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Data Engineering Data Engineer SQL Engineering 52

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. Data Engineer certification will aid in scaling up you knowledge and learning of data engineering.

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Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

DECEMBER 28, 2023

Its comprehensive suite of services can handle data at scale. It’s no surprise that the demand for certified Azure data engineers has skyrocketed. Today, Azure Data Engineer certification is an invaluable asset for those looking to excel in the field of data engineering. Who is an Azure Data Engineer?

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Data Engineering Podcast

DECEMBER 11, 2021

In this episode he explains how it can be used to build rich and useful profiles of your users, the system architecture that powers it, and some of the ways that it is being integrated into an organization’s broader data ecosystem. Missing data? Start trusting your data with Monte Carlo today! Stale dashboards?

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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. They store and manage current and historical data in a data warehouse.

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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. Data lakes offer a scalable and cost-effective solution.

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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. Data lakes offer a scalable and cost-effective solution.

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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. Data lakes offer a scalable and cost-effective solution.

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Data Management Management Data Lake Data Warehouse 52

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. Pharma Data Mesh Domains.

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Ascend.io

JANUARY 2, 2024

The key differentiation lies in the transformational steps that a data pipeline includes to make data business-ready. Ultimately, the core function of a pipeline is to take raw data and turn it into valuable, accessible insights that drive business growth. best suit our processed data? cleaning, formatting)?

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Data Pipeline Building Raw Data 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. What Is ELT? So, what exactly is ELT?

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Raw Data Data Warehouse Data Cleanse Data Integration 52

Monte Carlo

JUNE 28, 2022

To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader, is proud to announce integrations with Delta Lake and Databricks’ Unity Catalog for full data observability coverage. billion in 2020 to 17.60 billion in 2020 to 17.60

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Data Lake Metadata AWS Data Warehouse 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

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Data Pipeline Architecture Kafka AWS 52

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

Your downstream data consumers including product analysts, marketing leaders, and sales teams rely on data-driven tools like CRMs, CXPs, CMSs, and any other acronym under the sun to do their jobs quickly and effectively. But what happens when the data is wrong?

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ProjectPro

JUNE 9, 2021

This blog on Data Science vs. Data Engineering presents a detailed comparison between the two domains. vs. What does a Data Engineer do? Are you a Data Scientist or a Data Engineer? Is data engineering more important than data science?

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Data Engineering Data Engineer Engineering Amazon Web Services 52

Grouparoo

OCTOBER 26, 2021

Origin The origin of a data pipeline refers to the point of entry of data into the pipeline. This includes the different possible sources of data such as application APIs, social media, relational databases, IoT device sensors, and data lakes. Destinations can vary depending on the use case of the pipeline.

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Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

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Data Lake Data Warehouse Unstructured Data Raw Data 52

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

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ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

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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.

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U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Essentially, this is the difference between a lake and a warehouse. On the other hand, a data warehouse contains historical data that has been cleaned and arranged. .

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Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Knowledge Hut

OCTOBER 30, 2023

The role of a Power BI developer is extremely imperative as a data professional who uses raw data and transforms it into invaluable business insights and reports using Microsoft’s Power BI. Develop a long-term vision for Power BI implementation and data analytics. Who is a Power BI Developer?

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BI Business Intelligence Data Cleanse Business Analyst 52

Ascend.io

APRIL 12, 2023

For example, database queries / jobs often fail, leaving residual data that pollutes datasets and requires cleanup before you can rerun the query. This step includes the logging and alerting of errors that help focus the engineers who are intervening to resolve the problem. Have a data steward.

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Monte Carlo

NOVEMBER 14, 2023

Apache Iceberg is an open source data lakehouse table format developed by the data engineering team at Netflix to provide a faster and easier way to process large datasets at scale. It is designed to be easily queryable with SQL even for large analytic tables (we’re talking petabytes of data). Let’s dive in.

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Data Lake Metadata Data Warehouse SQL 64

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind.

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Data Lake Unstructured Data Data Warehouse Metadata 52

AltexSoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. What an analytics engineer is. Sounds interesting, right?

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Engineering Software Engineer Software Engineering Data Warehouse 59

Edureka

JUNE 13, 2024

Types of Query Folding in Power BI There are three ways a Query Folding statement could go: Full Query Folding: All your transformations are pushed to the source, and processing is done professionally at the Query engine. So, a part of the processing takes place in the query engine. What is the use of Query Folding in Power BI?

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BI Raw Data SQL Database 52

Towards Data Science

FEBRUARY 9, 2024

Eventing In many cases, the data platform itself needs to be responsible for, or at the very least inform, the generation of first party data. I break down eventing into two categories: Change Data Capture  — CDC The basic gist of CDC is using your database’s CRUD commands as a stream of data itself.

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Building Transportation Data Lake Metadata 76

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. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

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Engineering Raw Data Data Science Scala 87

Data Engineering Weekly

JANUARY 15, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today.

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Data Engineering Data Engineer Engineering Metadata 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.

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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. The ELT workflow. Scalability.

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Process Building Raw Data Data Lake 52

Grouparoo

AUGUST 3, 2021

The mission of many data teams is a very simple one. They seek to use data to help the business take smarter actions. The input is raw data from everywhere that touches the business. Because there are often many sources for the data, much of the work is often in data engineering. What is ETL?

Raw Data 52

Raw Data Data Warehouse SQL Coding 52

Towards Data Science

NOVEMBER 16, 2023

ELT comprises three main phases: Extract (E) : data is extracted from multiple sources in different formats, both structured and unstructured. Load (L) : data is loaded into a target destination, such as a data warehouse. Extract and Load This phase includes VDK jobs calling the Europeana REST API to extract raw data.

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Data Process Process Raw Data Data 72

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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