Analytics Vidhya

FEBRUARY 17, 2023

Introduction Are you curious about the latest advancements in the data tech industry? Perhaps you’re hoping to advance your career or transition into this field. In that case, we invite you to check out DataHour, a series of webinars led by experts in the field.

Analytics 319

Analytics Analytics Data Pipeline Data Warehouse 319

Women in Big Data

OCTOBER 9, 2024

The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline? A traditional data pipeline is a structured process that begins with gathering data from various sources and loading it into a data warehouse or data lake.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

Smart Data Collective

SEPTEMBER 26, 2021

The raw data can be fed into a database or data warehouse. An analyst can examine the data using business intelligence tools to derive useful information. . To arrange your data and keep it raw, you need to: Make sure the data pipeline is simple so you can easily move data from point A to point B.

Database 130

Database Data Visualization Big Data Big Data 130

Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. ETL is vital for ensuring data quality and integrity.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 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 Engineer Data Engineering Data Engineering 52

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. Read more to know.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

phData

JANUARY 5, 2023

On-Premises to The Cloud This type of migration involves moving an organization’s BI platform from an on-premises environment (such as a local server or data center) to a cloud-based environment. For example, suppose an organization moves from an on-premises database to a cloud-based database like Snowflake.

Analytics 52

Analytics Analytics Tableau Database 52

Pickl AI

JULY 25, 2024

Must Read Blogs: Exploring the Power of Data Warehouse Functionality. Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. It is commonly used in data warehouses for business analytics and reporting.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

phData

JANUARY 5, 2023

Connecting Snowflake to Python can be a game changer for your data services. Python can be used to migrate your data from a previous platform to Snowflake , create or manage data pipelines for Extract, Transform, and Load (ETL) processes, perform data science tasks such as machine learning or create data analysis visualizations.

Python 52

Python Data Engineering Data Engineering Data Engineering 52

phData

APRIL 28, 2025

For those unfamiliar with GIT or GIT practices, please refer Git for Business Users with Matillion DPC What is a Matillion Pipeline? A Matillion pipeline is a collection of jobs that extract, load, and transform (ETL/ELT) data from various sources into a target system, such as a cloud data warehouse like Snowflake.

AI 52

AI AI SQL ETL 52

Pickl AI

JULY 25, 2024

In this blog, we’ll delve into the intricacies of data ingestion, exploring its challenges, best practices, and the tools that can help you harness the full potential of your data. Batch Processing In this method, data is collected over a period and then processed in groups or batches.

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

IBM Journey to AI blog

AUGUST 4, 2023

Data fabric Data fabric architectures are designed to connect data platforms with the applications where users interact with information for simplified data access in an organization and self-service data consumption. This lets users across the organization treat the data like a product with widespread access.

Data Lakes 73

Data Lakes AI AI Data Governance 73

ODSC - Open Data Science

JANUARY 18, 2024

This individual is responsible for building and maintaining the infrastructure that stores and processes data; the kinds of data can be diverse, but most commonly it will be structured and unstructured data. They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

phData

JUNE 26, 2024

Cleaning and preparing the data Raw data typically shouldn’t be used in machine learning models as it’ll throw off the prediction. This can be achieved by, you guessed it, analyzing the data. What if you could know what drives them to buy your products and could use that to bring in more customers like them?

Machine Learning 52

Machine Learning Machine Learning Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 5, 2024

The Microsoft Certified: Azure Data Scientist Associate certification is highly recommended, as it focuses on the specific tools and techniques used within Azure. Additionally, enrolling in courses that cover Machine Learning, AI, and Data Analysis on Azure will further strengthen your expertise.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

ODSC - Open Data Science

APRIL 4, 2024

Find out how to weave data reliability and quality checks into the execution of your data pipelines and more. Dagster+ Launch April 12th, NYC and San Francisco Join us for the unveiling of Dagster+, the next generation of Dagster Cloud.

Data Visualization 52

Data Visualization Analytics Analytics Big Data Analytics 52

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

Pickl AI

DECEMBER 9, 2024

Hive is a data warehouse tool built on Hadoop that enables SQL-like querying to analyse large datasets. What is the Difference Between Structured and Unstructured Data? Structured data is organised in tabular formats like databases, while unstructured data, such as images or videos, lacks a predefined format.

Big Data 52

Big Data Big Data Hadoop Apache Kafka 52

Mlearning.ai

MARCH 15, 2023

I have checked the AWS S3 bucket and Snowflake tables for a couple of days and the Data pipeline is working as expected. The scope of this article is quite big, we will exercise the core steps of data science, let's get started… Project Layout Here are the high-level steps for this project. The data is in good shape.

Python 52

Python AWS Exploratory Data Analysis Machine Learning 52

phData

JANUARY 15, 2024

These tools are supercharged assistants, offering advanced visualizations, intelligent alerts, and in-depth log data analysis. They complement Snowflake by creating a central hub for managing logs, monitoring performance, and assessing overall data health.

Data Governance 52

Data Governance Database Data Warehouse Cloud Computing 52

Mlearning.ai

JULY 10, 2023

Using Scheduled Queries is a smart choice for regular reporting, data analysis, and other processing tasks. In case of complex data pipelines, a combination of Materialized Views, Stored Procedures, and Scheduled Queries could be a better choice than to solely rely on Scheduled Queries by itself.

SQL 52

SQL Database Database Administration Data Lakes 52

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. The existing Data Catalog becomes the Default catalog (identified by the AWS account number) and is readily available in SageMaker Lakehouse.

SQL 128

SQL Data Analyst Data Warehouse AWS 128