Data Science Blog

NOVEMBER 15, 2023

The lower part of the iceberg is barely visible to the normal analyst on the tool interface, but is essential for implementation and success: this is the Event Log as the data basis for graph and data analysis in Process Mining. The creation of this data model requires the data connection to the source system (e.g.

Data Models 245

Data Models Data Modeling Business Intelligence Business Intelligence 245

Flipboard

MARCH 22, 2023

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. For more information about prerequisites, see Get Started with Data Wrangler.

AWS 123

AWS Data Preparation Azure Data Scientist 123

Smart Data Collective

APRIL 29, 2020

Redshift is the product for data warehousing, and Athena provides SQL data analytics. AWS Glue helps users to build data catalogues, and Quicksight provides data visualisation and dashboard construction. The services from AWS can be catered to meet the needs of each business user. Microsoft Azure.

Data Warehouse 99

Data Warehouse SQL Azure ETL 99

O'Reilly Media

SEPTEMBER 15, 2021

Cloud certifications, specifically in AWS and Microsoft Azure, were most strongly associated with salary increases. As we’ll see later, cloud certifications (specifically in AWS and Microsoft Azure) were the most popular and appeared to have the largest effect on salaries. The top certification was for AWS (3.9%

AI 145

AI AI Azure AWS 145

Women in Big Data

NOVEMBER 27, 2024

How to Choose a Data Warehouse for Your Big Data Choosing a data warehouse for big data storage necessitates a thorough assessment of your unique requirements. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

Smart Data Collective

JANUARY 10, 2023

For enjoying all the benefits that IoT technologies can offer us today, it is vital to find a place where all the gathered data will be kept. Usually, companies choose a platform provided by one of the most well-known vendors like Amazon (AWS), Google Cloud, or Microsoft Azure. Proceed to data analysis.

Business Intelligence 124

Business Intelligence Business Intelligence Internet of Things Analytics 124

ODSC - Open Data Science

FEBRUARY 2, 2023

Being able to discover connections between variables and to make quick insights will allow any practitioner to make the most out of the data. Analytics and Data Analysis Coming in as the 4th most sought-after skill is data analytics, as many data scientists will be expected to do some analysis in their careers.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

DrivenData Labs

NOVEMBER 14, 2023

For example, the Google Earth API can be used to access Landsat , MODIS , VIIRS , GEDI , and SMAP data. To get started, check out the Earth Engine installation instructions and Python API introduction VEDA Dashboard : VEDA (Visualization, Exploration, and Data Analysis) is NASA's open-source Earth Science platform in the cloud.

Python 162

Python AWS Azure Data Analysis 162

Smart Data Collective

SEPTEMBER 21, 2021

With the amount of increase in data, the complexity of managing data only keeps increasing. It has been found that data professionals end up spending 75% of their time on tasks other than data analysis. Advantages of data fabrication for data management. Data quality and governance.

Data Quality 131

Data Quality Data Pipeline Database Internet of Things 131

Towards AI

JULY 17, 2023

Colab allows anybody to write and execute arbitrary python code through the browser, and is especially well suited to machine learning, data analysis and education. More technically, Colab is a hosted Jupyter notebook service that requires no setup to use, while providing access free of charge to computing resources including GPUs”.

Machine Learning 98

Machine Learning Machine Learning Data Analysis Data Analysis 98

Becoming Human

MAY 15, 2023

These communities will help you to be updated in the field, because there are some experienced data scientists posting the stuff, or you can talk with them so they will also guide you in your journey. Data Analysis After learning math now, you are able to talk with your data.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Data Science Connect

JULY 26, 2023

Unlike traditional cloud computing, where data is sent to centralized data centers, edge computing brings processing closer to the data source. This proximity significantly reduces latency and enhances real-time data analysis, making it indispensable for applications like IoT, autonomous vehicles, smart cities, and more.

Data Scientist 100

Data Scientist Internet of Things Cloud Computing Azure 100

Towards AI

FEBRUARY 5, 2024

Here is a short list of the possibilities built-in loaders allow: loading specific file types (JSON, CSV, pdf) or a folder path (DirectoryLoader) in general with selected file types use pre-existent integration with cloud providers (Azure, AWS, Google, etc.) connect to applications (Slack, Notion, Figma, Wikipedia, etc.).

Azure 115

Azure Data Analysis Data Analysis AWS 115

Data Science Dojo

JULY 3, 2024

Here’s a list of key skills that are typically covered in a good data science bootcamp: Programming Languages : Python : Widely used for its simplicity and extensive libraries for data analysis and machine learning. R : Often used for statistical analysis and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Smart Data Collective

MAY 19, 2021

Back-end System for Data Acquisition, Storage, and Analytics. Amazon, for instance, provides an entire suite of services that allow developers to integrate connectivity into hardware, design scalable home automation solutions , and apply advanced machine learning algorithms while conducting sensor data analysis.

AI 134

AI AI Analytics Analytics 134

ODSC - Open Data Science

FEBRUARY 17, 2023

Knowing how spaCy works means little if you don’t know how to apply core NLP skills like transformers, classification, linguistics, question answering, sentiment analysis, topic modeling, machine translation, speech recognition, named entity recognition, and others. Google Cloud is starting to make a name for itself as well.

Deep Learning 111

Deep Learning Deep Learning Data Science Natural Language Processing 111

ODSC - Open Data Science

APRIL 3, 2023

We looked at over 25,000 job descriptions, and these are the data analytics platforms, tools, and skills that employers are looking for in 2023. Excel is the second most sought-after tool in our chart as you’ll see below as it’s still an industry standard for data management and analytics.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

IBM Journey to AI blog

NOVEMBER 13, 2023

As an open-source system, Kubernetes services are supported by all the leading public cloud providers, including IBM, Amazon Web Services (AWS), Microsoft Azure and Google. While Docker includes its own orchestration tool, called Docker Swarm , most developers choose Kubernetes container orchestration instead.

Machine Learning 129

Machine Learning Machine Learning ML ML 129

phData

FEBRUARY 21, 2025

A data warehouse enables advanced analytics, reporting, and business intelligence. The data warehouse emerged as a means of resolving inefficiencies related to data management, data analysis, and an inability to access and analyze large volumes of data quickly.

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

IBM Journey to AI blog

JANUARY 10, 2023

For this data scenario, the current flight delay data (2019 – 2022) is contained in a regular, internal NPS database table residing in an NPS as a Service (NPSaaS) instance within the U.S. The external table capability of NPS makes it transparent to a client that some of the data resides externally to the data warehouse.

Data Warehouse 52

Data Warehouse Data Analysis Data Analysis SQL 52

Mlearning.ai

MAY 23, 2023

Blind 75 LeetCode Questions - LeetCode Discuss Data Manipulation and Analysis Proficiency in working with data is crucial. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA).

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JANUARY 13, 2025

Key Skills Experience with cloud platforms (AWS, Azure). Proficiency in Data Analysis tools for market research. Data Engineer Data Engineers build the infrastructure that allows data generation and processing at scale. Knowledge of tools like Pandas , NumPy , and big data frameworks (e.g.,

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. How would you segment customers based on their purchasing behaviour?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Mlearning.ai

JANUARY 28, 2023

It has a wide range of features, including data preprocessing, feature extraction, deep learning training, and model evaluation. Pandas: Pandas is a powerful data analysis library that makes it easy to work with datasets of any size or shape. To build a data science or machine learning project 2. To work with big data 7.

Machine Learning 52

Machine Learning Machine Learning Data Science ML 52

O'Reilly Media

NOVEMBER 28, 2023

AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. How will AI adopters react when the cost of renting infrastructure from AWS, Microsoft, or Google rises? Given the cost of equipping a data center with high-end GPUs, they probably won’t attempt to build their own infrastructure.

AI 135

AI AI Data Analysis Data Analysis 135

Mlearning.ai

JULY 11, 2023

For example, when it comes to deploying projects on cloud platforms, different companies may utilize different providers like AWS, GCP, or Azure. Therefore, having proficiency in a specific cloud platform, such as Azure, does not mean you will exclusively work with that platform in the industry.

Data Science 40

Data Science Exploratory Data Analysis Azure Power BI 40

The MLOps Blog

MARCH 20, 2023

Data Backup and Recovery : Have a data storage platform that supports a contingency plan for unexpected data loss and deletion, which can be quite common in a long-duration project. Data Compression : Explore data compression techniques to optimize storage space, primarily as long-term ML projects collect more data.

ML 59

ML ML Machine Learning Machine Learning 59

Pickl AI

JULY 25, 2023

At the core of Data Science lies the art of transforming raw data into actionable information that can guide strategic decisions. Role of Data Scientists Data Scientists are the architects of data analysis. They clean and preprocess the data to remove inconsistencies and ensure its quality.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

phData

SEPTEMBER 14, 2023

Many enterprises, large or small, are storing data in cloud object storage like AWS S3, Azure ADLS Gen2, or Google Bucket because it offers scalable and cost-effective solutions for managing vast amounts of data. However, there are business reasons why you need to start your data analysis with external tables.

Data Analysis 52

Data Analysis Data Analysis SQL Azure 52

Pickl AI

NOVEMBER 4, 2024

Data Warehousing A data warehouse is a centralised repository that stores large volumes of structured and unstructured data from various sources. It enables reporting and Data Analysis and provides a historical data record that can be used for decision-making.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

JANUARY 26, 2023

In the most generic terms, every project starts with raw data, which comes from observations and measurements i.e. it is directly downloaded from instruments. It can be gradually “enriched” so the typical hierarchy of data is thus: Raw data ↓ Cleaned data ↓ Analysis-ready data ↓ Decision-ready data ↓ Decisions.

AWS 98

AWS Database Data Science Clean Data 98

ODSC - Open Data Science

JANUARY 18, 2024

Like with any professional shift, it’s always good practice to take inventory of your existing data science strengths. Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. With that said, each skill may be used in a different manner.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JULY 30, 2024

The University of Nottingham offers a Master of Science in Bioinformatics, which is aimed at students with a background in biological sciences who wish to develop skills in bioinformatics, statistics, computer programming , and Data Analytics. Familiarise yourself with data analysis tools such as RStudio, Jupyter Notebook, and Excel.

Cloud Computing 52

Cloud Computing Machine Learning Machine Learning Power BI 52

phData

SEPTEMBER 19, 2023

Thankfully, there are tools available to help with metadata management, such as AWS Glue, Azure Data Catalog, or Alation, that can automate much of the process. What are the Best Data Modeling Methodologies and Processes? Data lakes are meant to be flexible for new incoming data, whether structured or unstructured.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

ODSC - Open Data Science

JANUARY 29, 2024

Data Engineering A job role in its own right, this involves managing the modern data stack and structuring data and workflow pipelines — crucial for preparing data for use in training and running AI models. series (Davinci, etc), GPT-4, and GPT-4 Turbo are immensely popular.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

Pickl AI

NOVEMBER 28, 2024

Cloud platforms like AWS , Google Cloud Platform (GCP), and Microsoft Azure provide managed services for Machine Learning, offering tools for model training, storage, and inference at scale. Scalability Considerations Scalability is a key concern in model deployment.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

NOVEMBER 27, 2024

R for Data Science Although not as broadly adopted as Python, R holds a strong position in Data Science, particularly for statistical analysis, advanced visualisation, and specialised techniques. Data Science Platforms Platforms like Databricks and Apache Zeppelin offer robust support for multi-language workflows.

Data Science 52

Data Science Python Machine Learning Machine Learning 52