Flipboard

JANUARY 6, 2025

Helping government agencies adopt AI and ML technologies Precise works closely with AWS to offer end-to-end cloud services such as enterprise cloud strategy, infrastructure design, cloud-native application development, modern data warehouses and data lakes, AI and ML, cloud migration, and operational support.

AWS 65

AWS ML ML Machine Learning 65

ODSC - Open Data Science

FEBRUARY 24, 2023

Apache Superset remains popular thanks to how well it gives you control over your data. Algorithm-visualizer GitHub | Website Algorithm Visualizer is an interactive online platform that visualizes algorithms from code. The no-code visualization builds are a handy feature.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Dataconomy

FEBRUARY 12, 2024

ELT advocates for loading raw data directly into storage systems, often cloud-based, before transforming it as necessary. This shift leverages the capabilities of modern data warehouses, enabling faster data ingestion and reducing the complexities associated with traditional transformation-heavy ETL processes.

ETL 195

ETL Data Governance Machine Learning Machine Learning 195

IBM Journey to AI blog

SEPTEMBER 11, 2023

Data and AI as the Pillars of the Partnership At the heart of this partnership lies a deep appreciation for the role of data as the catalyst for AI innovation. Data is the fuel that powers AI algorithms, enabling them to generate insights, predictions, and solutions that drive businesses forward.

AWS 121

AWS Data Warehouse AI AI 121

IBM Journey to AI blog

OCTOBER 30, 2023

Real-time data analytics helps in quick decision-making, while advanced forecasting algorithms predict product demand across diverse locations. AWS’s scalable infrastructure allows for rapid, large-scale implementation, ensuring agility and data security.

AWS 95

AWS Data Warehouse AI AI 95

phData

NOVEMBER 4, 2024

Combined with the visual data prep interface, this allows users to seamlessly add derived variables without leaving the platform, significantly reducing the time to valuable insights. Together, Snowflake and Dataiku empower organizations to build sophisticated, data-driven solutions quickly and at scale.

Machine Learning 69

Machine Learning Machine Learning Data Science ML 69

Smart Data Collective

NOVEMBER 18, 2020

Data mining is an automated data search based on the analysis of huge amounts of information. Complex mathematical algorithms are used to segment data and estimate the likelihood of subsequent events. Every Data Scientist needs to know Data Mining as well, but about this moment we will talk a bit later.

Data Mining 144

Data Mining Data Mining Data Mining Data Science 144

Dataconomy

SEPTEMBER 4, 2023

Predictive analytics: Predictive analytics leverages historical data and statistical algorithms to make predictions about future events or trends. Machine learning and AI analytics: Machine learning and AI analytics leverage advanced algorithms to automate the analysis of data, discover hidden patterns, and make predictions.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

IBM Journey to AI blog

SEPTEMBER 19, 2023

Business users will also perform data analytics within business intelligence (BI) platforms for insight into current market conditions or probable decision-making outcomes. Many functions of data analytics—such as making predictions—are built on machine learning algorithms and models that are developed by data scientists.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Smart Data Collective

JULY 20, 2021

These software tools rely on sophisticated big data algorithms and allow companies to boost their sales, business productivity and customer retention. 10 Panoply: In the world of CRM technology, Panoply is a data warehouse build that automates data collection, query optimization and storage management.

Big Data 142

Big Data Big Data ETL Analytics 142

Towards AI

FEBRUARY 21, 2023

Image by the Author: AI business use cases Defining Artificial Intelligence Artificial Intelligence (AI) is a term used to describe the development of robust computer systems that can think and react like a human, possessing the ability to learn, analyze, adapt and make decisions based on the available data.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence AI AI 98

Mlearning.ai

FEBRUARY 16, 2023

The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency. In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

phData

MAY 12, 2023

KNIME Analytics Platform is an open-source, user-friendly software enabling users to create data science applications and services intuitively, without coding knowledge. Its visual interface allows you to design workflows, handle data extraction and transformation, and apply statistical methods or machine learning algorithms.

Data Warehouse 72

Data Warehouse Machine Learning Machine Learning Database 72

Pickl AI

OCTOBER 17, 2024

Introduction ETL plays a crucial role in Data Management. This process enables organisations to gather data from various sources, transform it into a usable format, and load it into data warehouses or databases for analysis. Loading The transformed data is loaded into the target destination, such as a data warehouse.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

Tableau

FEBRUARY 14, 2022

The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse. This modern, cloud-based data stack enables you to have all your data in one place while unlocking both backward-looking, historical analysis as well as forward-looking scenario planning and predictive analysis.

AI 98

AI AI Tableau Data Scientist 98

AWS Machine Learning Blog

OCTOBER 9, 2024

Using Amazon CloudWatch for anomaly detection Amazon CloudWatch supports creating anomaly detectors on specific Amazon CloudWatch Log Groups by applying statistical and ML algorithms to CloudWatch metrics. Use AWS Glue Data Quality to understand the anomaly and provide feedback to tune the ML model for accurate detection.

AWS 89

AWS ML ML Data Quality 89

Dataconomy

MAY 10, 2023

Predictive analytics: Open source BI software can use algorithms and machine learning to analyze historical data and identify patterns that can be used to predict future trends and outcomes. The software also offers a suite of integrated tools, making it an all-in-one solution for data scientists and BI executives.

Business Intelligence 178

Business Intelligence Business Intelligence Power BI Data Analysis 178

phData

SEPTEMBER 19, 2023

A rigid data model such as Kimball or Data Vault would ruin this flexibility and essentially transform your data lake into a data warehouse. However, some flexible data modeling techniques can be used to allow for some organization while maintaining the ease of new data additions.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

Tableau

FEBRUARY 14, 2022

The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse. This modern, cloud-based data stack enables you to have all your data in one place while unlocking both backward-looking, historical analysis as well as forward-looking scenario planning and predictive analysis.

AI 95

AI AI Tableau Data Scientist 95

AWS Machine Learning Blog

APRIL 4, 2024

The analyst is given direct access to the raw data or through our data warehouse. We do this using dedicated algorithms and models developed by us for analyzing the specific characteristics of the channels. We also discovered inefficient pipeline runs and scheduling algorithms for the models.

AWS 96

AWS Machine Learning Machine Learning ML 96

Dataconomy

APRIL 27, 2023

The role of digit-computers in the digital age Handle multi-user access & data integrity OLTP systems must be able to handle multiple users accessing the same data simultaneously while ensuring data integrity. An OLAP database may also be organized as a data warehouse.

Database 159

Database Data Scientist Data Mining Data Mining 159

IBM Journey to AI blog

SEPTEMBER 11, 2023

enhances data management through automated insights generation, self-tuning performance optimization and predictive analytics. It leverages machine learning algorithms to continuously learn and adapt to workload patterns, delivering superior performance and reducing administrative efforts.

Database 101

Database SQL Data Warehouse Machine Learning 101

phData

JUNE 18, 2024

How to Prepare Data for Use in Machine Learning Models Data Collection The first step is to collect all the data you believe the model will need and ingest it into a centralized location, such as a data warehouse. We need to format it to be suitable for machine learning algorithms.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

The MLOps Blog

MAY 17, 2023

Focus Area ETL helps to transform the raw data into a structured format that can be easily available for data scientists to create models and interpret for any data-driven decision. A data pipeline is created with the focus of transferring data from a variety of sources into a data warehouse.

ETL 59

ETL Data Pipeline ML ML 59

Pickl AI

AUGUST 9, 2024

Data Warehousing Solutions Tools like Amazon Redshift, Google BigQuery, and Snowflake enable organisations to store and analyse large volumes of data efficiently. Students should learn about the architecture of data warehouses and how they differ from traditional databases.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

AWS Machine Learning Blog

MAY 8, 2024

Concurrently, the ensemble model strategically combines the strengths of various algorithms. SageMaker Feature Store – By using a centralized repository for ML features, SageMaker Feature Store enhances data consumption and facilitates experimentation with validation data.

ML 120

ML ML AWS AI 120

ODSC - Open Data Science

OCTOBER 25, 2024

Building an Open, Governed Lakehouse with Apache Iceberg and Apache Polaris (Incubating) Yufei Gu | Senior Software Engineer | Snowflake In this session, you’ll explore how open-source table formats are revolutionizing data architectures by enabling the power and efficiency of data warehouses within data lakes.

AI 52

AI AI Data Scientist Data Lakes 52

IBM Journey to AI blog

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Alation

MAY 16, 2023

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

AWS Machine Learning Blog

MAY 25, 2023

The Step Functions Data Science SDK is used to analyze and compare multiple model training algorithms. Model training is run, with multiple algorithms and several combinations of hyperparameters utilizing the YAML configuration file. The training step function is designed to have heavy parallelism.

AWS 78

AWS ML ML Data Science 78

Dataconomy

SEPTEMBER 27, 2023

Data analysts collect, clean, and analyze data to extract insights that can help businesses make better decisions. Data scientists develop and apply machine learning algorithms to solve complex data problems. Machine learning developers develop and train machine learning algorithms.

Database Administration 113

Database Administration Database Azure Cloud Computing 113

Alation

FEBRUARY 13, 2020

By matching landmarks on the human face or identifying patterns in speech rate, pitch range, intensity, and voice quality, AI is able to detect human emotions — some algorithms can even detect 10-different emotions. AI is not a fad, algorithmic decision-making is inevitable. Human Curation + Machine Learning.

Machine Learning 52

Machine Learning Machine Learning Analytics Analytics 52

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. in a 2D space based on the machine learning algorithm used.

Python 52

Python Database SQL Machine Learning 52

Precisely

MARCH 10, 2023

At the same time, IoT devices, web analytics, social media, and interconnected systems generate higher volumes of data than ever before. Think back to the early 2000s, a time of big data warehouses with rigid structures. There was a massive expansion of efforts to design and deploy big data technologies.

Analytics 59

Analytics Analytics Data Warehouse Big Data 59

ODSC - Open Data Science

MAY 29, 2023

Turning your Data/AI algorithms into full web apps in no time with Taipy Alexandre Sajus | Co-Founder | Taipy Florian Jacta Customer Success Manager | Taipy In the Python open-source ecosystem, many packages are available that cater to the building of great algorithms and the visualization of data. Ask the Experts!

Machine Learning 52

Machine Learning Machine Learning Data Science AI 52

Smart Data Collective

JANUARY 22, 2020

However, according to Forbes research, unsecured Facebook databases leakages affected more than 419 million users.The principles of virtual technology pose potential threats to the information security of cloud computing associated with the use of shared data warehouses. Encrypted data is available after authentication only.

Cloud Computing 74

Cloud Computing Data Warehouse Database Algorithm 74