Data Science Dojo

OCTOBER 31, 2024

Specialized Industry Knowledge The University of California, Berkeley notes that remote data scientists often work with clients across diverse industries. Whether it’s finance, healthcare, or tech, each sector has unique data requirements. This role builds a foundation for specialization.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. Thats where data engineering tools come in!

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Hacker News

NOVEMBER 19, 2024

Here are a few of the things that you might do as an AI Engineer at TigerEye: - Design, develop, and validate statistical models to explain past behavior and to predict future behavior of our customers’ sales teams - Own training, integration, deployment, versioning, and monitoring of ML components - Improve TigerEye’s existing metrics collection and (..)

Computer Science 145

Computer Science Computer Science ML ML 145

AWS Machine Learning Blog

NOVEMBER 13, 2024

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

ML 112

ML ML AWS Data Preparation 112

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Data Science Blog

SEPTEMBER 19, 2023

Streamlined Collaboration Among Teams Data Warehouse Systems in the cloud often involve cross-functional teams — data engineers, data scientists, and system administrators. This ensures that the data models and queries developed by data professionals are consistent with the underlying infrastructure.

Data Warehouse 259

Data Warehouse Azure SQL Database 259

phData

DECEMBER 18, 2023

Data engineering refers to the design of systems that are capable of collecting, analyzing, and storing data at a large scale. In manufacturing, data engineering aids in optimizing operations and enhancing productivity while ensuring curated data that is both compliant and high in integrity.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

phData

AUGUST 11, 2023

Data engineering in healthcare is taking a giant leap forward with rapid industrial development. However, data collection and analysis have been commonplace in the healthcare sector for ages. Data Engineering in day-to-day hospital administration can help with better decision-making and patient diagnosis/prognosis.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Read more to know.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

MAY 16, 2023

Data engineering is a rapidly growing field that designs and develops systems that process and manage large amounts of data. There are various architectural design patterns in data engineering that are used to solve different data-related problems.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

DataSeries

AUGUST 15, 2024

Enrich data engineering skills by building problem-solving ability with real-world projects, teaming with peers, participating in coding challenges, and more. Globally several organizations are hiring data engineers to extract, process and analyze information, which is available in the vast volumes of data sets.

Data Engineer 40

Data Engineer Data Engineering Data Engineering Data Engineering 40

Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Data Intelligence emerges as the indispensable force steering businesses towards informed and strategic decision-making. These insights?

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

phData

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. What is a Data Lake?

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

Smart Data Collective

MAY 29, 2023

The rate of growth at which world economies are growing and developing thanks to new technologies in information data and analysis means that companies are needing to prepare accordingly. As a result of the benefits of business analytics , the demand for Data analysts is growing quickly.

Data Analyst 104

Data Analyst SQL Data Scientist Data Analysis 104

Pickl AI

JUNE 5, 2025

In the Indian context, data scientists often work in dynamic environments such as IT services, fintech, e-commerce, healthcare, and telecom sectors. They are expected to be versatile, handling everything from data engineering and exploratory analysis to deploying machine learning models and communicating insights to business stakeholders.

Data Scientist 52

Data Scientist Data Science Power BI Machine Learning 52

Tableau

JULY 25, 2024

Spencer Czapiewski July 25, 2024 - 5:54pm Thomas Nhan Director, Product Management, Tableau Lari McEdward Technical Writer, Tableau Expand your data modeling and analysis with Multi-fact Relationships, available with Tableau 2024.2. You may have heard of Multi-fact Relationships informally referred to as “shared dimensions.”

Tableau 76

Tableau Data Models Data Modeling Data Silos 76

Pickl AI

APRIL 22, 2025

Introduction A snowflake schema is a sophisticated data modeling technique used in data warehousing to efficiently organize and store large volumes of data. It is an extension of the star schema, designed to optimize storage, enhance data integrity, and support complex analytical queries.

Data Warehouse 52

Data Warehouse Data Models Data Modeling Analytics 52

AWS Machine Learning Blog

MARCH 18, 2025

RAG is a framework for building generative AI applications that can make use of enterprise data sources and vector databases to overcome knowledge limitations. RAG works by using a retriever module to find relevant information from an external data store in response to a users prompt.

SQL 106

SQL Database AI AI 106

ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

Azure 52

Azure ML ML Data Modeling 52

Mlearning.ai

MARCH 3, 2023

Data Engineering A data engineers start to simplification Introduction A lot of time folks start directly jumping into KPIs ( Key Performace Indicators) without understanding the need for those KPIs. I have met with clients who have dumped all the data they had and never figured out what they really wanted to achieve.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

Thats why we use advanced technology and data analytics to streamline every step of the homeownership experience, from application to closing. Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL. Apache HBase was employed to offer real-time key-based access to data.

Data Science 75

Data Science AWS Hadoop Data Scientist 75

Data Science Blog

AUGUST 22, 2024

Real-Time Data Processing Businesses are adopting technologies that can process and analyze data instantly due to the need for real-time insights. Real-time data preparation tools allow companies to react quickly to new information, maintaining a competitive edge in fast-paced industries.

Data Preparation 130

Data Preparation Data Quality AI AI 130

Dataversity

SEPTEMBER 28, 2022

Data engineering is a fascinating and fulfilling career – you are at the helm of every business operation that requires data, and as long as users generate data, businesses will always need data engineers. The journey to becoming a successful data engineer […].

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. For more information, see Zeta Global’s home page. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

AWS 121

AWS Machine Learning Machine Learning ML 121

IBM Journey to AI blog

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. Data scientists will typically perform data analytics when collecting, cleaning and evaluating data.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Tableau

SEPTEMBER 23, 2021

For example, Tableau data engineers want a single source of truth to help avoid creating inconsistencies in data sets, while line-of-business users are concerned with how to access the latest data for trusted analysis when they need it most. Data modeling. Data migration . Data architecture.

Data Governance 102

Data Governance Analytics Analytics Tableau 102

phData

FEBRUARY 8, 2024

Data Modeling, dbt has gradually emerged as a powerful tool that largely simplifies the process of building and handling data pipelines. dbt is an open-source command-line tool that allows data engineers to transform, test, and document the data into one single hub which follows the best practices of software engineering.

Data Models 52

Data Models Data Modeling Data Warehouse Database 52

Tableau

SEPTEMBER 23, 2021

For example, Tableau data engineers want a single source of truth to help avoid creating inconsistencies in data sets, while line-of-business users are concerned with how to access the latest data for trusted analysis when they need it most. Data modeling. Data migration . Data architecture.

Data Governance 97

Data Governance Analytics Analytics Tableau 97

DataRobot

FEBRUARY 22, 2021

DataRobot’s team of elite data scientists and thought leaders have created, curated, and taught rigorous courses that empower 10X Academy students to take control of their future by gaining the skills required to solve complex problems. For a complete list of graduates, including their contact information, visit the Meet Our Graduates page.

Data Science 52

Data Science Data Scientist Citizen Data Scientist Data Analyst 52

ODSC - Open Data Science

MAY 10, 2023

Data-centric AI, in his opinion, is based on the following principles: It’s time to focus on the data — after all the progress achieved in algorithms means it’s now time to spend more time on the data Inconsistent data labels are common since reasonable, well-trained people can see things differently.

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

Dataconomy

MAY 2, 2023

These techniques can be utilized to estimate the likelihood of future events and inform the decision-making process. Data modeling involves identifying underlying data structures, identifying patterns, and filling in gaps where data is nonexistent. How data engineers tame Big Data?

ML 110

ML ML Machine Learning Machine Learning 110

AWS Machine Learning Blog

OCTOBER 20, 2023

Collectively, these modules address governance across various dimensions, such as infrastructure, data, model, and cost. Reference architecture modules The reference architecture comprises eight modules, each designed to solve a specific set of problems.

ML 132

ML ML AWS Data Lakes 132

phData

MAY 25, 2023

This way, each of your contextual data points used for filtering are stored in memory. This permits you to only pull the data necessary to make decisions while allowing you to stay updated on the latest information and maintain report performance levels.

Power BI 84

Power BI Analytics Analytics Azure 84

ODSC - Open Data Science

APRIL 26, 2023

Though seen in a variety of industries, including finance, eCommerce, marketing, healthcare, and government, a data analyst can be expected to perform analysis and interpretation of complex data to help organizations make informed decisions.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52

Alation

JULY 19, 2022

The traditional data science workflow , as defined by Joe Blitzstein and Hanspeter Pfister of Harvard University, contains 5 key steps: Ask a question. Get the data. Explore the data. Model the data. A data catalog can assist directly with every step, but model development.

Data Scientist 59

Data Scientist Data Quality Data Science Data Analyst 59

Alation

FEBRUARY 20, 2020

By changing the cost structure of collecting data, it increased the volume of data stored in every organization. Additionally, Hadoop removed the requirement to model or structure data when writing to a physical store. You did not have to understand or prepare the data to get it into Hadoop, so people rarely did.

Data Lakes 52

Data Lakes Hadoop Tableau Big Data 52

Mlearning.ai

FEBRUARY 16, 2023

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. The tool’s high storage capacity is perfect for keeping large information volumes.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52