Data Science Dojo

SEPTEMBER 11, 2024

With this full-fledged solution, you don’t have to spend all your time and effort combining different services or duplicating data. Overview of One Lake Fabric features a lake-centric architecture, with a central repository known as OneLake.

Power BI 306

Power BI Data Pipeline Data Warehouse Data Engineering 306

Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data. Big Data Architect.

SQL 159

SQL AWS Data Lakes AI 159

AWS Machine Learning Blog

AUGUST 8, 2024

Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries. This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock.

SQL 125

SQL Data Lakes Data Analyst AWS 125

Smart Data Collective

DECEMBER 13, 2022

There are several choices to consider, each with its own set of advantages and disadvantages: Data warehouses are used to store data that has been processed for a specific function from one or more sources. Data lakes hold raw data that has not yet been altered to meet a specific purpose. Prioritize.

Data Analysis 145

Data Analysis Data Analysis Analytics Analytics 145

Dataconomy

FEBRUARY 25, 2025

Use cases of big data Organizations across various industries leverage big data to enhance their operations and strategic decision-making processes. Healthcare In healthcare, big data helps professionals detect disease patterns, making it essential for diagnosing and improving patient care through advanced data analysis.

Big Data 91

Big Data Big Data Data Lakes Machine Learning 91

AWS Machine Learning Blog

NOVEMBER 12, 2024

NOTE : Output ETF names do not represent the actual data in the dataset used in this demonstration. What would the LLM’s response or data analysis be when the user’s questions in industry specific natural language get more complex? However, there is room for improvement in the analysis of data from structured datasets.

SQL 112

SQL AWS AI AI 112

Data Science Connect

JULY 28, 2023

Cloud-Based IoT Platforms Cloud-based IoT platforms offer scalable storage and computing resources for handling the massive influx of IoT data. These platforms provide data engineers with the flexibility to develop and deploy IoT applications efficiently.

Internet of Things 130

Internet of Things Data Engineer Data Engineering Data Engineering 130

ODSC - Open Data Science

MARCH 21, 2025

While its core solver is commercial, it supports multiple open-source projects, including Python libraries that help data scientists and operations researchers implement optimization solutions. ProspectiveReal-Time Streaming Analytics Prospective is an innovative open-source platform for real-time data analysis and visualization.

Data Scientist 52

Data Scientist Data Visualization Data Science Data Lakes 52

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. These tools will help make your initial data exploration process easy.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Data Lakes 145

Hacker News

JANUARY 26, 2024

This allows data to be read into DuckDB and moved between these systems in a convenient manner. In modern data analysis, data must often be combined from a wide variety of different sources. Data might sit in CSV files on your machine, in Parquet files in a data lake, or in an operational database.

Database 173

Database Data Analysis Data Analysis Data Lakes 173

Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. Well, let’s find out. Artificial intelligence (AI). Thank you for taking the time to read this blog post.

AWS 138

AWS Cloud Computing Data Lakes Database 138

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

Alation

FEBRUARY 13, 2020

Data catalogs have quickly become a core component of modern data management. Organizations with successful data catalog implementations see remarkable changes in the speed and quality of data analysis, and in the engagement and enthusiasm of people who need to perform data analysis. Conclusion.

Data Lakes 64

Data Lakes Data Analysis Data Analysis Big Data 64

IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Organizations can expect to reap the following benefits from implementing OLAP solutions, including the following.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

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

IBM Journey to AI blog

DECEMBER 18, 2023

Raw data feeds sound nice, but they usually end up creating more work for network teams, who have to process and analyze the data to discover the underlying cause of network issues. DNS Insights is a set of pre-built dashboards that do most of the data analysis work for you. In short, it is what you will actually use.

Data Analysis 89

Data Analysis Data Analysis Data Lakes 89

Pickl AI

DECEMBER 2, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

IBM Journey to AI blog

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Lakes 73

Data Lakes AI AI Data Governance 73

Tableau

APRIL 18, 2022

Data integration. Gain useful insights from data stored across different platforms and data sources, such as data warehouses, data lakes, and CRMs. Increase understanding of data sets on hand for data integration or data analysis. Virtualization and discovery. Orchestration.

Tableau 102

Tableau Data Quality Analytics Analytics 102

ODSC - Open Data Science

JULY 27, 2023

Choosing a Data Lake Format: What to Actually Look For The differences between many data lake products today might not matter as much as you think. When choosing a data lake, here’s something else to consider. Use this guide to get started with your prompt engineering skills!

Data Lakes 52

Data Lakes SQL AI AI 52

Pickl AI

NOVEMBER 25, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Tableau

APRIL 18, 2022

Data integration. Gain useful insights from data stored across different platforms and data sources, such as data warehouses, data lakes, and CRMs. Increase understanding of data sets on hand for data integration or data analysis. Virtualization and discovery. Orchestration.

Tableau 98

Tableau Data Quality Analytics Analytics 98

Women in Big Data

NOVEMBER 27, 2024

Security features include data encryption and access control. Integrating seamlessly with other Google Cloud services, BigQuery is a powerful solution for organizations seeking efficient and cost-effective large-scale data analysis. architecture for both structured and unstructured data.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

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

Alation

FEBRUARY 20, 2020

Data lakes, while useful in helping you to capture all of your data, are only the first step in extracting the value of that data.

Data Lakes 40

Data Lakes ETL Data Analyst Data Preparation 40

Pickl AI

FEBRUARY 21, 2023

Understanding the appropriate ways to use data remains critical to success in finance, education and commerce. Accordingly, data collection from numerous sources is essential before data analysis and interpretation. The gathering of data requires assessment and research from various sources.

Data Mining 52

Data Mining Data Mining Data Mining Data Scientist 52

AWS Machine Learning Blog

JUNE 25, 2024

The customer review analysis workflow consists of the following steps: A user uploads a file to dedicated data repository within your Amazon Simple Storage Service (Amazon S3) data lake, invoking the processing using AWS Step Functions. The Step Functions workflow starts.

AWS 126

AWS Natural Language Processing Machine Learning Machine Learning 126

ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform. Check them out for free!

AI 52

AI AI Data Science Machine Learning 52

Pickl AI

OCTOBER 6, 2024

ELT, which stands for Extract, Load, Transform, is a data integration process that shifts the sequence of operations seen in ETL. In ELT, data is extracted from its source and then loaded into a storage system, such as a data lake or data warehouse , before being transformed. Conversely, ELT flips this sequence.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

Pickl AI

JULY 6, 2023

Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis. It applies the data structure during querying rather than data ingestion. This delay makes Hive less suitable for real-time or interactive data analysis. Why Do We Need Hadoop Hive?

Hadoop 52

Hadoop SQL Big Data Big Data 52

Pickl AI

JULY 25, 2024

Data Ingestion Meaning At its core, It refers to the act of absorbing data from multiple sources and transporting it to a destination, such as a database, data warehouse, or data lake. 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

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

Pickl AI

AUGUST 1, 2023

Key Components of Data Engineering Data Ingestion : Gathering data from various sources, such as databases, APIs, files, and streaming platforms, and bringing it into the data infrastructure. Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

JULY 11, 2023

What are the similarities and differences between data centers, data lake houses, and data lakes? Data centers, data lake houses, and data lakes are all related to data storage and management, but they have some key differences. Not a cloud computer?

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

Pickl AI

JANUARY 28, 2025

This involves several key processes: Extract, Transform, Load (ETL): The ETL process extracts data from different sources, transforms it into a suitable format by cleaning and enriching it, and then loads it into a data warehouse or data lake. Data Lakes: These store raw, unprocessed data in its original format.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Pickl AI

SEPTEMBER 5, 2024

Storage Solutions: Secure and scalable storage options like Azure Blob Storage and Azure Data Lake Storage. Key features and benefits of Azure for Data Science include: Scalability: Easily scale resources up or down based on demand, ideal for handling large datasets and complex computations.

Azure 52

Azure Data Scientist Data Science Machine Learning 52