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.

Machine Learning 74

Machine Learning Building Datasets Big Data 74

Christophe Blefari

APRIL 21, 2023

If a model do not respect a contract it will not build. In dbt vocabulary build means run + other things. Building a ChatGPT Plugin for Medium. Fast News ⚡️ Building a Flink self-serve platform on Kubernetes at scale — Instacart engineering team migrated from Flink on EMR to Flink on Kubernetes.

Raw Data 130

Raw Data Data SQL Datasets 130

AltexSoft

MAY 12, 2022

Commercial audio sets for machine learning are definitely more reliable in terms of data integrity than free ones. The same relates to those who buy annotated sound collections from data providers. Audio data labeling. Building an app for snore and teeth grinding detection. Commercial datasets.

Machine Learning 122

Machine Learning Building Deep Learning Datasets 122

Monte Carlo

JANUARY 6, 2023

A data-informed product strategy Product teams are tasked with being data-informed at all stages in the product life cycle, from idea generation and product definition, to validating prototypes and building a commercially successful product. But so often data is not a first-class citizen in product launches.

Building 52

Building Project BI Data 52

Snowflake

APRIL 7, 2023

This was the first year that startups had the chance to build with our Native Applications Framework (currently in private preview), and we were thrilled to see the number of entries that included a native app. It transforms multiple financial and operational systems’ raw data into a common, friendly data model that people can understand.

Raw Data 111

Raw Data Portfolio Building SQL 111

Snowflake

MAY 23, 2024

Welcome to Snowflake’s Startup Spotlight, where we ask startup founders about the problems they’re solving, the apps they’re building and the lessons they’ve learned during their startup journey. One last question: What advice would you give to other entrepreneurs thinking about building apps on Snowflake?

Data Pipeline 88

Data Pipeline Raw Data Data Schemas Technology 88

Monte Carlo

JANUARY 12, 2023

Today, we have a data team of about 20 professionals organized among three teams. The first team is responsible for building the backend data infrastructure. The second team, data services , are more application or front-end oriented. Also, Snowflake scalability and features like data sharing were very attractive.

Architecture 52

Architecture Building Data Warehouse BI 52

Monte Carlo

NOVEMBER 21, 2024

You’re maintaining two systems, so your data team needs to be agile enough to work with different technologies while keeping their data definitions consistent. Want to run SQL queries on your structured data while also keeping raw files for your data scientists to play with? The downside?

Data Pipeline 52

Data Pipeline Designing Lambda Architecture Kafka 52

dbt Developer Hub

DECEMBER 5, 2021

We’ve also included some sample raw data to add to your warehouse so you can run these projects yourself! It's more important to think about how features build upon themselves (and each other) rather than how quickly they do so.* You can use this repository to benchmark the maturity of your own dbt project.

Project 52

Project Building Metadata BI 52

Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Data Engineering Podcast listeners can sign up for a free 2-week sandbox account, go to dataengineeringpodcast.com/tonic today to give it a try!

Data Management 100

Data Management Management MongoDB Scala 100

Monte Carlo

FEBRUARY 9, 2023

For those unfamiliar, data vault is a data warehouse modeling methodology created by Dan Linstedt (you may be familiar with Kimball or Imon models ) created in 2000 and updated in 2013. Data vault collects and organizes raw data as underlying structure to act as the source to feed Kimball or Inmon dimensional models.

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Striim

AUGUST 7, 2024

Transform Raw Data into AI-generated Actions and Insights in Seconds In today’s fast-paced business environment, the ability to quickly transform raw data into actionable insights is crucial. POS transactions training data span 79 days starting from (2024-02-01 to 2024-04-20).

IT 52

IT Entertainment MySQL Raw Data 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. You’ll learn how to load, query, and process your data.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Meltano

OCTOBER 5, 2022

This includes various day-to-day activities, from reducing development time and improving data quality to providing guidance and support to data team members. This involves continually striving to reduce wasted effort, identify gaps and correct them, and improve data development and deployment processes. The best part?

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

Precisely

JANUARY 5, 2023

For some companies that do have a formal strategy, that strategy may be little more than a technical exercise, the primary purpose of which is to lay out the nuts and bolts of data management, compliance, and similar baseline requirements. Data governance plays a critical role in any effective data strategy.

Data Governance 52

Data Governance Government Data Raw Data 52

dbt Developer Hub

SEPTEMBER 28, 2022

So let’s say that you have a business question, you have the raw data in your data warehouse , and you’ve got dbt up and running. If your analyst is not trained as an analytics engineer, this is the point that they will need to hand the project over to a data engineer to build the model. Or are you?

Engineering 52

Engineering Raw Data Datasets BI 52

Edureka

SEPTEMBER 23, 2024

Data Science vs Artificial Intelligence: Key Differences Aspect Data Science Artificial Intellignce Definition An academic discipline that involves the study of facts and figures and aims at their interpretation. The question of data science vs AI: Which one is better?

Data Science 40

Data Science Data Mining Computer Science Finance 40

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. While car companies lowered costs using mass production, companies in 2021 put data engineers and data scientists on the assembly line. Imagine if a car company asked the engineers who designed cars to also build them.

Engineering 61

Engineering Raw Data SQL Data Engineering 61

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.

Business Intelligence 52

Business Intelligence BI Data Mining Algorithm 52

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 Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

The Modern Data Company

MAY 10, 2023

Companies need more than definitions. In a world where technology evolves, and data assets have exploded in volume, it helps to know the best use cases for each of these solutions and when to avoid them. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Monte Carlo

MARCH 10, 2022

Monte Carlo’s Barr Moses sat down with Snowflake Director of Product Management Chris Child to talk about building data platforms at scale, how awesome data teams approach data quality, the role of data observability tools in the modern data stack, and more. Just get the raw data in there.

Engineering 52

Engineering Management Raw Data Scala 52

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.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Companies need more than definitions. In a world where technology evolves, and data assets have exploded in volume, it helps to know the best use cases for each of these solutions and when to avoid them. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Companies need more than definitions. In a world where technology evolves, and data assets have exploded in volume, it helps to know the best use cases for each of these solutions and when to avoid them. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 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.

Data Integration 52

Data Integration Data Governance Government Raw Data 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.

SQL 64

SQL Data Science Machine Learning Algorithm 64

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 Raw Data 52

RandomTrees

DECEMBER 20, 2023

Thus, Edge AI reduces downtime or latency by combining Edge computing and AI processes. Furthermore, next gen edge computing devices successfully integrate AI processes as an essential component. As a result, users can build data and support user requirements without interacting with physical locations, saving them time and money.

IT 52

IT Hospitality Healthcare Deep Learning 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 Engineer Data Engineering Engineering 52

Knowledge Hut

NOVEMBER 27, 2023

A Data Scientist earns about 25% more than a computer programmer. A person with a die-hard passion to work on large datasets and to draw meaningful insights can definitely begin their journey in becoming a great data scientist. What is Data in Data Science? Data is the essence of Data Science.

Data Science 52

Data Science Datasets Machine Learning Portfolio 52

phData: Data Engineering

SEPTEMBER 27, 2024

Instead of trying to build a perfect, complete customer model from the get-go, it starts with small, standardized pieces of information – let’s call them data atoms (or atomic data). Building Blocks of Customer Understanding: Data Atoms Explained So, what exactly is a customer data atom?

Data 52

Data Raw Data Data Lake Architecture 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. However, the medallion architecture brings a clear bucketing of data to align with the organization's delivery strategy from raw data → filer & clean data, → business metrics.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

DataKitchen

FEBRUARY 2, 2023

And the tools for acting on data are consolidating: Tableau does data prep, Altreyx does data science, Qlik joined with Talend, etc. Most data governance tools today start with the slow, waterfall building of metadata with data stewards and then hope to use that metadata to drive code that runs in production.

Metadata 52

Metadata BI Government Data Science 52

Airbnb Tech

APRIL 13, 2021

The path to cloud efficiency begins with a cost data foundation by Anna Matlin and Tamar Eterman Introduction Business profitability and sustainability are powerful reasons to invest in infrastructure efficiency, but it is easy to feel lost about how to actually reduce costs. Most teams at Airbnb rely on the data warehouse (i.e.,

AWS 52

AWS Raw Data Amazon Web Services Cloud 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

Mutt Data

APRIL 4, 2023

We’ve gone over the game-changing benefits of implementing a Modern Data Stack and hopefully established that it is a necessary foundation for companies to effectively scale and eventually build ML and AI capabilities upon to gain a competitive advantage. But there are definitely points to look out for: Embrace raw data!

Raw Data 40

Raw Data Data Warehouse AWS Data 40