Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

Big Data 52

Big Data Machine Learning Algorithm Data Scientist 52

ODSC - Open Data Science

JUNE 19, 2023

With the advent of big data in the modern world, RTOS is becoming increasingly important. As software expert Tim Mangan explains, a purpose-built real-time OS is more suitable for apps that involve tons of data processing. The Big Data and RTOS connection IoT and embedded devices are among the biggest sources of big data.

Big Data 96

Big Data ETL Artificial Intelligence Artificial Intelligence 96

Marktechpost

JUNE 13, 2024

ELT Pipelines: Typically used for big data, these pipelines extract data, load it into data warehouses or lakes, and then transform it. ELT Pipelines: Typically used for big data, these pipelines extract data, load it into data warehouses or lakes, and then transform it.

ETL 130

ETL Machine Learning Data Ingestion Big Data 130

Unite.AI

DECEMBER 5, 2023

In this digital economy, data is paramount. Today, all sectors, from private enterprises to public entities, use big data to make critical business decisions. However, the data ecosystem faces numerous challenges regarding large data volume, variety, and velocity. Enter data warehousing!

Metadata 162

Metadata Big Data ETL Data Mining 162

Pickl AI

JULY 30, 2024

Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation. With a user-friendly interface and robust features, NiFi simplifies complex data workflows and enhances real-time data integration. What is Apache NiFi?

Data Ingestion 52

Data Ingestion ETL Big Data Data Integration 52

Pickl AI

OCTOBER 10, 2024

Introduction Data transformation plays a crucial role in data processing by ensuring that raw data is properly structured and optimised for analysis. Data transformation tools simplify this process by automating data manipulation, making it more efficient and reducing errors.

ETL 52

ETL Data Quality Business Intelligence Big Data 52

Pickl AI

NOVEMBER 4, 2024

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. ETL is vital for ensuring data quality and integrity.

Data Quality 52

Data Quality ETL Data Integration Machine Learning 52

ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

Data Science 52

Data Science ETL Data Scientist Data Quality 52

Flipboard

JUNE 26, 2023

Transform raw insurance data into CSV format acceptable to Neptune Bulk Loader , using an AWS Glue extract, transform, and load (ETL) job. When the data is in CSV format, use an Amazon SageMaker Jupyter notebook to run a PySpark script to load the raw data into Neptune and visualize it in a Jupyter notebook.

Auto-complete 123

Auto-complete ML Auto-classification ETL 123

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 130

Data Quality Metadata ETL Big Data 130

Marktechpost

JUNE 5, 2024

You can optimize your costs by using data profiling to find any problems with data quality and content. Fixing poor data quality might otherwise cost a lot of money. The 18 best data profiling tools are listed below. It comes with an Informatica Data Explorer function to meet your data profiling requirements.

Data Quality 113

Data Quality Metadata Data Integration ETL 113

ODSC - Open Data Science

SEPTEMBER 27, 2023

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. Unlike traditional data warehouses or relational databases, data lakes accept data from a variety of sources, without the need for prior data transformation or schema definition.

Big Data 98

Big Data Metadata ETL Business Intelligence 98

TransOrg Analytics

AUGUST 9, 2024

Data Quality: Without proper governance, data quality can become an issue. Performance: Query performance can be slower compared to optimized data stores. Business Applications: Big Data Analytics : Supporting advanced analytics, machine learning, and artificial intelligence applications.

Machine Learning 52

Machine Learning ETL Big Data Data Analysis 52

Marktechpost

AUGUST 27, 2024

This article lists the top data analysis courses that can help you build the essential skills needed to excel in this rapidly growing field. Introduction to Data Analytics This course provides a comprehensive introduction to data analysis, covering the roles of data professionals, data ecosystems, and Big Data tools like Hadoop and Spark.

Data Analysis 59

Data Analysis Python ETL Big Data 59

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 Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Science 52

Data Science Data Scientist ETL Machine Learning 52

Unite.AI

SEPTEMBER 22, 2023

Jay Mishra is the Chief Operating Officer (COO) at Astera Software , a rapidly-growing provider of enterprise-ready data solutions. Automation has been a key trend in the past few years and that ranges from the design to building of a data warehouse to loading and maintaining, all of that can be automated.

Large Language Models 278

Large Language Models Automation Artificial Intelligence Artificial Intelligence 278

AWS Machine Learning Blog

NOVEMBER 12, 2024

The first step in developing and deploying generative AI use cases is having a well-defined data strategy. Their data pipeline (as shown in the following architecture diagram) consists of ingestion, storage, ETL (extract, transform, and load), and a data governance layer. Agmatix’s technology architecture is built on AWS.

Generative AI 110

Generative AI Prompt Engineer Prompt Engineering AI 110

TransOrg Analytics

AUGUST 21, 2024

Such success stories have largely depended on Data Engineering processes. This article explores how data engineering can improve Customer 360 initiatives for AWS data engineering , big data engineering, and data analytics companies. Tools Used: AWS glue for data integration and transformation.

ETL 52

ETL Big Data Engineer Data Ingestion Data Integration 52

Marktechpost

JULY 23, 2023

Big data analytics are supported by scalable, object-oriented services. Each of the “buckets” used to store data has a maximum capacity of 5 terabytes. is a cloud-based data integration platform to create simple, visualized data pipelines for your data warehouse. Integrate.io Integrate.io

Machine Learning 52

Machine Learning ETL Big Data Data Integration 52

Bugra Akyildiz

JUNE 29, 2024

This week, I will cover why I think data janitor work is dying and companies that are built in on top of data janitor work could be ripe for disruption through LLMs and what to do about it. A data janitor is a person who works to take big data and condense it into useful amounts of information.

LLM 40

LLM Big Data Data Quality ETL 40

The MLOps Blog

MARCH 15, 2023

Some of the popular cloud-based vendors are: Hevo Data Equalum AWS DMS On the other hand, there are vendors offering on-premise data pipeline solutions and are mostly preferred by organizations dealing with highly sensitive data. Hevo automatically detects and duplicates the schema at the data destination.

ETL 59

ETL Categorization Automation Data Integration 59

Pickl AI

NOVEMBER 15, 2023

Data scientists can explore, experiment, and derive valuable insights without the constraints of a predefined structure. This capability empowers organizations to uncover hidden patterns, trends, and correlations in their data, leading to more informed decision-making. What Is a Data Warehouse? What is meant by Data Lake?

ETL 52

ETL Metadata Business Intelligence Data Analysis 52

Artificial Corner

JUNE 6, 2023

Timeline of data engineering — Created by the author using canva In this post, I will cover everything from the early days of data storage and relational databases to the emergence of big data, NoSQL databases, and distributed computing frameworks. MongoDB, developed by MongoDB Inc.,

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

Pickl AI

APRIL 26, 2024

During a data analysis project, I encountered a significant data discrepancy that threatened the accuracy of our analysis. I conducted thorough data validation, collaborated with stakeholders to identify the root cause, and implemented corrective measures to ensure data integrity.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

Marktechpost

JULY 17, 2023

Panoply Panoply is a cloud-based, intelligent end-to-end data management system that streamlines data from source to analysis without using ETL. Panoply offers the tools for data integration, linking, transformation, warehousing, and more as an all-encompassing data management system.

Data Mining 96

Data Mining Machine Learning Data Scientist Artificial Intelligence 96

Flipboard

NOVEMBER 24, 2023

The SnapLogic Intelligent Integration Platform (IIP) enables organizations to realize enterprise-wide automation by connecting their entire ecosystem of applications, databases, big data, machines and devices, APIs, and more with pre-built, intelligent connectors called Snaps.

ETL 156

ETL Prompt Engineer Prompt Engineering Generative AI 156

Pickl AI

JULY 18, 2024

In contrast, MongoDB uses a more straightforward query language that works well with JSON data structures. MongoDB’s horizontal scaling capabilities surpass relational databases’ typical vertical scaling limitations, making it suitable for big data applications. How Does MongoDB Perform Data Validation?

Explainability 52

Explainability ETL Data Science Python 52

Pickl AI

JUNE 11, 2024

Let’s delve into the key components that form the backbone of a data warehouse: Source Systems These are the operational databases, CRM systems, and other applications that generate the raw data feeding the data warehouse. Data Extraction, Transformation, and Loading (ETL) This is the workhorse of architecture.

ETL 52

ETL Data Mining Actionable Intelligence Data Integration 52

AWS Machine Learning Blog

AUGUST 2, 2024

About the authors Vicente Cruz Mínguez is the Head of Data & Advanced Analytics at Cepsa Química. He has more than 8 years of experience with big data and machine learning projects in financial, retail, energy, and chemical industries. The following diagram illustrates this architecture.

Generative AI 116

Generative AI LLM Machine Learning Data Scientist 116