Towards Data Science

FEBRUARY 9, 2024

In truth, the synergy between batch and streaming pipelines is essential for tackling the diverse challenges posed to your data platform at scale. The key to seamlessly addressing these challenges lies, unsurprisingly, in data orchestration. Their robust core offering seamlessly integrates data warehouses with data-hungry applications.

Building 82

Building Transportation Data Lake Metadata 82

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. How Does AWS Glue Work?

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AWS Scala Metadata Data Lake 98

Maxime Beauchemin

JANUARY 7, 2018

When functions are “pure” — meaning they do not have side-effects — they can be written, tested, reasoned-about and debugged in isolation, without the need to understand external context or history of events surrounding its execution. But how do we model this in a functional data warehouse without mutating data?

Data Engineering 183

Data Engineering Data Engineer Data Process Process 183

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Raw Data 70

Raw Data Data Business Intelligence High Quality Data 70

AltexSoft

DECEMBER 23, 2022

It is a data integration process with which you first extract raw information (in its original formats) from various sources and load it straight into a central repository such as a cloud data warehouse , a data lake , or a data lakehouse where you transform it into suitable formats for further analysis and reporting.

Process 52

Process Building Raw Data Data Lake 52

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. 2023 predictions from the panel are; Unified metadata becomes kingmaker. RudderStack builds your CDP on top of your data warehouse, giving you a more secure and cost-effective solution.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Cloudera Data Warehouse (CDW) is here to save the day! CDW is an integrated data warehouse service within Cloudera Data Platform (CDP).

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IT Data Lake Data Warehouse Cloud Storage 93

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

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?

Engineering 82

Engineering Raw Data Data Science Scala 82

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. They also recently acquired Apache Flink , another streaming solution.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Monte Carlo

AUGUST 30, 2023

Often, teams run custom data tests as part of a deployment pipeline, or scheduled on production systems via job schedulers like Apache Airflow, dbt Cloud, or via in-built schedulers in your data warehouse solution. Once the models are created and data transformed, `dbt test` should be executed. Curious to learn more?

SQL 52

SQL Datasets Database High Quality Data 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Airbnb Tech

JUNE 1, 2021

When a metric is defined in Minerva, authors are required to provide important self-describing metadata. Prior to Minerva, all such metadata often existed only as undocumented institutional knowledge or in chart definitions scattered across various business intelligence tools.

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Datasets Pipeline-centric Metadata Data Science 52

Data Engineering Podcast

JANUARY 28, 2018

Go to dataengineeringpodcast.com/aicon-new-york to register and save 20% If you work with data or want to learn more about how the projects you have heard about on the show get used in the real world then join me at the Open Data Science Conference in Boston from May 1st through the 4th.

Data 100

Data Project Electronics Data Management 100

ProjectPro

AUGUST 21, 2015

Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. Data that can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi-structured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

AltexSoft

MAY 12, 2023

There are several widely used unstructured data storage solutions such as data lakes (e.g., MongoDB, Cassandra), and big data processing frameworks (e.g., Also, modern cloud data warehouses and data lakehouses may be good options for the same purposes. Invest in data governance. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Rockset

SEPTEMBER 6, 2019

Virtual Reality – The Next Frontier in Media I work as a Data Engineer at a leading company in the VR space, with a mission to capture and transmit reality in perfect fidelity. Our content varies from on-demand experiences to live events like NBA games, comedy shows and music concerts.

Metadata 40

Metadata Kafka Data Cleanse SQL 40

DoorDash Engineering

APRIL 12, 2023

As we mentioned in our previous blog , we began with a ‘Bring Your Own SQL’ method, in which data scientists checked in ad-hoc Snowflake (our primary data warehouse) SQL files to create metrics for experiments, and metrics metadata was provided as JSON configs for each experiment.

SQL 82

SQL Metadata Raw Data Government 82

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.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Monte Carlo

JANUARY 4, 2024

Data processing : Whatnot data teams rely on Snowflake and dbt for processing, with orchestration in Dagster. It’s quite dynamic, and analytics events that represent ephemeral things happening in real time are incredibly valuable for us. Data quality challenges at Whatnot And you know what they say: mo’ data, mo’ problems.

Data 40

Data Metadata Software Engineer Software Engineering 40

Monte Carlo

AUGUST 19, 2023

With companies moving their data platforms to the cloud, the emergence of cloud-native solutions ( data warehouse vs data lake or even a data lakehouse ) have taken over the market, offering more accessible and affordable options for storing data relative to many on-premises solutions.

Building 52

Building BI Data Lake Data Governance 52