Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineering 195

Data Engineering Data Engineering Data Engineering Data Engineer 195

Data Science Connect

JANUARY 27, 2023

In this blog post, we will be discussing 7 tips that will help you become a successful data engineer and take your career to the next level. Learn SQL: As a data engineer, you will be working with large amounts of data, and SQL is the most commonly used language for interacting with databases.

Data Engineering 130

Data Engineering Data Engineering Data Engineering Data Engineer 130

Flipboard

DECEMBER 11, 2024

Organizations are building data-driven applications to guide business decisions, improve agility, and drive innovation. Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Choose the plus sign and for Notebook , choose Python 3.

SQL 160

SQL AWS Data Lakes AI 160

How to Learn Machine Learning

APRIL 26, 2025

Data can be generated from databases, sensors, social media platforms, APIs, logs, and web scraping. Data can be in structured (like tables in databases), semi-structured (like XML or JSON), or unstructured (like text, audio, and images) form. Deployment and Monitoring Once a model is built, it is moved to production.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

Data Science 101

NOVEMBER 7, 2019

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Python support has been available for a while. Azure Synapse.

Data Science 106

Data Science Azure SQL Machine Learning 106

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Data Warehouse 97

Data Warehouse SQL Azure ETL 97

phData

NOVEMBER 28, 2024

“ Vector Databases are completely different from your cloud data warehouse.” – You might have heard that statement if you are involved in creating vector embeddings for your RAG-based Gen AI applications. This process is repeated until the entire text is divided into coherent segments. Return the chunks as an ARRAY.

Python 52

Python Database SQL Machine Learning 52

Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. If you are prompted to choose a kernel, choose Data Science as the image and Python 3 as the kernel, then choose Select.

ML 123

ML ML AWS Data Warehouse 123

ODSC - Open Data Science

FEBRUARY 24, 2023

These tools will help make your initial data exploration process easy. ydata-profiling GitHub | Website The primary goal of ydata-profiling is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Output is a fully self-contained HTML application.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

ODSC - Open Data Science

AUGUST 23, 2023

Run pandas at scale on your data warehouse Most enterprise data teams store their data in a database or data warehouse, such as Snowflake, BigQuery, or DuckDB. Ponder solves this problem by translating your pandas code to SQL that can be understood by your data warehouse.

Data Warehouse 52

Data Warehouse Data Science Database SQL 52

Analytics Vidhya

JANUARY 2, 2023

While not all of us are tech enthusiasts, we all have a fair knowledge of how Data Science works in our day-to-day lives. All of this is based on Data Science which is […]. The post Step-by-Step Roadmap to Become a Data Engineer in 2023 appeared first on Analytics Vidhya.

Data Engineering 329

Data Engineering Data Engineering Data Engineering Data Engineer 329

phData

SEPTEMBER 2, 2024

Matillion is a SaaS-based data integration platform that can be hosted in AWS, Azure, or GCP. It offers a cloud-agnostic data productivity hub called Matillion Data Productivity Cloud. Below is a sample scenario for 3 business units within an organization for the data mart layer of the data warehouse.

ETL 52

ETL Data Warehouse SQL Database 52

Hacker News

AUGUST 27, 2024

Policy Zones has been built into different Meta systems, including: Function-based systems that load, process, and propagate data through stacks of function calls in different programming languages. Batch-processing systems that process data rows in batch (mainly via SQL ). When data flows across different systems (e.g.,

Data Warehouse 169

Data Warehouse Database SQL Machine Learning 169

phData

AUGUST 9, 2023

With ELT, we first extract data from source systems, then load the raw data directly into the data warehouse before finally applying transformations natively within the data warehouse. This is unlike the more traditional ETL method, where data is transformed before loading into the data warehouse.

ETL 52

ETL Data Warehouse Cloud Data Big Data 52

IBM Journey to AI blog

JANUARY 10, 2023

This allows data that exists in cloud object storage to be easily combined with existing data warehouse data without data movement. The advantage to NPS clients is that they can store infrequently used data in a cost-effective manner without having to move that data into a physical data warehouse table.

Data Warehouse 52

Data Warehouse Data Analysis Data Analysis SQL 52

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

phData

MARCH 31, 2023

With Hex , it has never been easier to unlock insights from your data. In this blog, we will dive deeper into the capabilities of Snowpark for Python and how combining with Hex supports data science by providing faster and more efficient data processing and analytics capabilities on top of Hex’s easy notebook collaboration and sharing.

Data Science 59

Data Science Machine Learning Machine Learning Python 59

phData

AUGUST 22, 2024

Snowflake Cortex stood out as the ideal choice for powering the model due to its direct access to data, intuitive functionality, and exceptional performance in handling SQL tasks. uses: actions/setup-python@v4 with: python-version: '3.10' - name: Install dependencies run: | python -m pip install --upgrade pip pip install -r./python/requirements.txt

SQL 52

SQL Data Quality Python Data Warehouse 52

The MLOps Blog

JANUARY 26, 2024

Related article How to Build ETL Data Pipelines for ML See also MLOps and FTI pipelines testing Once you have built an ML system, you have to operate, maintain, and update it. All of them are written in Python. They store their feature data in Hopsworks’ free serverless platform, app.hopsworks.ai.

Machine Learning 72

Machine Learning Machine Learning ML ML 72

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Warehousing: Amazon Redshift, Google BigQuery, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

MARCH 3, 2025

Summary: Business Intelligence Analysts transform raw data into actionable insights. They use tools and techniques to analyse data, create reports, and support strategic decisions. Key skills include SQL, data visualization, and business acumen. Introduction We are living in an era defined by data.

Business Intelligence 52

Business Intelligence Business Intelligence Data Analyst Data Visualization 52

Dataconomy

SEPTEMBER 27, 2024

It was my first job as a data analyst. It helped me to become familiar with popular tools such as Excel and SQL and to develop my analytical thinking. The time I spent at Renault helped me realize that data analytics is something I would be interested in pursuing as a full-time career.

Analytics 113

Analytics Analytics Big Data Big Data 113

The MLOps Blog

OCTOBER 20, 2023

Example template for an exploratory notebook | Source: Author How to organize code in Jupyter notebook For exploratory tasks, the code to produce SQL queries, pandas data wrangling, or create plots is not important for readers. If a reviewer wants more detail, they can always look at the Python module directly.

SQL 52

SQL Database Data Scientist Python 52

Pickl AI

OCTOBER 17, 2024

It is a data integration process that involves extracting data from various sources, transforming it into a suitable format, and loading it into a target system, typically a data warehouse. ETL is the backbone of effective data management, ensuring organisations can leverage their data for informed decision-making.

ETL 52

ETL Data Warehouse SQL Data Quality 52

Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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. Your skill set should include the ability to write in the programming languages Python, SAS, R and Scala. And you should have experience working with big data platforms such as Hadoop or Apache Spark.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

IBM Journey to AI blog

JULY 17, 2023

Within watsonx.ai, users can take advantage of open-source frameworks like PyTorch, TensorFlow and scikit-learn alongside IBM’s entire machine learning and data science toolkit and its ecosystem tools for code-based and visual data science capabilities.

AI 74

AI AI Machine Learning Machine Learning 74

Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

APRIL 6, 2023

Strong programming language skills in at least one of the languages like Python, Java, R, or Scala. Having experience using at least one end-to-end Azure data lake project. Hands-on experience working with SQLDW and SQL-DB. Knowledge in using Azure Data Factory Volume. Azure Databricks and Azure Storage Services.

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52

IBM Journey to AI blog

NOVEMBER 3, 2023

When you make it easier to work with events, other users like analysts and data engineers can start gaining real-time insights and work with datasets when it matters most. As a result, you reduce the skills barrier and increase your speed of data processing by preventing important information from getting stuck in a data warehouse.

Apache Kafka 79

Apache Kafka Data Warehouse Data Pipeline Big Data 79

phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Pickl AI

JULY 3, 2023

Here are steps you can follow to pursue a career as a BI Developer: Acquire a solid foundation in data and analytics: Start by building a strong understanding of data concepts, relational databases, SQL (Structured Query Language), and data modeling.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

phData

OCTOBER 17, 2024

Airflow is entirely in Python, so it’s relatively easy for those with some Python experience to get started using it. dbt offers a SQL-first transformation workflow that lets teams build data transformation pipelines while following software engineering best practices like CI/CD, modularity, and documentation.

AI 52

AI AI SQL Data Quality 52

AWS Machine Learning Blog

JUNE 25, 2024

In addition, the generative business intelligence (BI) capabilities of QuickSight allow you to ask questions about customer feedback using natural language, without the need to write SQL queries or learn a BI tool. The raw data is processed by an LLM using a preconfigured user prompt. The LLM generates output based on the user prompt.

AWS 126

AWS Natural Language Processing Machine Learning Machine Learning 126