Dataconomy

MARCH 4, 2025

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Businesses across various sectors are leveraging data mining to gain a competitive edge, improve decision-making, and optimize operations.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

ODSC - Open Data Science

SEPTEMBER 29, 2023

In today’s digital world, data is king. Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate.

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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 126

SQL Data Lakes Data Analyst AWS 126

Smart Data Collective

OCTOBER 27, 2021

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Druid is a real-time analytics database from Apache.

Analytics 130

Analytics Analytics Data Warehouse Business Intelligence 130

phData

NOVEMBER 9, 2023

A cloud data warehouse is designed to combine a concept that every organization knows, namely a data warehouse, and optimizes the components of it, for the cloud. What is a Data Lake? A Data Lake is a location to store raw data that is in any format that an organization may produce or collect.

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Data Warehouse Data Lakes Clustering Cloud Data 98

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. With Great Expectations , data teams can express what they “expect” from their data using simple assertions.

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Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

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. Defining OLAP today OLAP database systems have significantly evolved since their inception in the early 1990s.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. architecture for both structured and unstructured data. Its PostgreSQL foundation ensures compatibility with most SQL clients.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

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

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

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. 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

Pickl AI

APRIL 9, 2025

The importance of ETL tools is underscored by their ability to handle diverse data sources, from relational databases to cloud-based services. This capability allows organizations to consolidate disparate data into a unified repository for analytics and reporting, providing insights that can drive strategic decisions.

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

IBM Journey to AI blog

JULY 3, 2024

Modernizing your data infrastructure to hybrid cloud for applications, analytics and gen AI Adopting multicloud and hybrid strategies is becoming mandatory, requiring databases that support flexible deployments across the hybrid cloud. This ensures you have a data foundation that grows with your data needs, wherever your data resides.

AI 45

AI AI Data Quality Database 45

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

AWS Machine Learning Blog

JUNE 25, 2024

To create and share customer feedback analysis without the need to manage underlying infrastructure, Amazon QuickSight provides a straightforward way to build visualizations, perform one-time analysis, and quickly gain business insights from customer feedback, anytime and on any device. The Step Functions workflow starts.

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AWS Natural Language Processing Machine Learning Machine Learning 127

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

ODSC - Open Data Science

JUNE 12, 2023

They all agree that a Datamart is a subject-oriented subset of a data warehouse focusing on a particular business unit, department, subject area, or business functionality. The Datamart’s data is usually stored in databases containing a moving frame required for data analysis, not the full history of data.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

DagsHub

NOVEMBER 11, 2024

Types of Unstructured Data As unstructured data grows exponentially, organisations face the challenge of processing and extracting insights from these data sources. Unlike structured data, unstructured data doesn’t fit neatly into predefined models or databases, making it harder to analyse using traditional methods.

AI 52

AI AI Data Lakes Database 52

ODSC - Open Data Science

NOVEMBER 19, 2024

Dimensional Data Modeling in the Modern Era by Dustin Dorsey Slides Dustin Dorsey’s AI slides explored the evolution of dimensional data modeling, a staple in data warehousing and business intelligence.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

ODSC - Open Data Science

JANUARY 30, 2024

Think of it as building plumbing for data to flow smoothly throughout the organization. EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Mlearning.ai

FEBRUARY 16, 2023

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. Snowflake data cloud provides IP whitelisting to restrict access to data to authorized users.

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Data Warehouse Business Intelligence Business Intelligence 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. Explore: How Business Intelligence helps in Decision Making.

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Data Warehouse Business Intelligence Business Intelligence Database 52

Pickl AI

OCTOBER 10, 2024

Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or Business Intelligence tools. This makes drawing actionable insights, spotting patterns, and making data-driven decisions easier.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Data Warehouse Cloud Data Analytics Analytics 58

IBM Journey to AI blog

OCTOBER 16, 2023

This type of next-generation data store combines a data lake’s flexibility with a data warehouse’s performance and lets you scale AI workloads no matter where they reside. It allows for automation and integrations with existing databases and provides tools that permit a simplified setup and user experience.

AI 88

AI AI Data Warehouse ML 88

IBM Journey to AI blog

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. Similarly, the relational database has been the foundation for data warehousing for as long as data warehousing has been around.

Data Warehouse 58

Data Warehouse Data Engineering Data Engineering Data Engineer 58

AWS Machine Learning Blog

NOVEMBER 15, 2023

After a few minutes, a transcript is produced with Amazon Transcribe Call Analytics and saved to another S3 bucket for processing by other business intelligence (BI) tools. PCA’s security features ensure that any PII data was redacted from the transcript, as well as from the audio file itself.

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AWS Analytics Analytics ML 118

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 Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

IBM Journey to AI blog

JULY 17, 2023

Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent. 1 Watsonx.data offers built-in governance and automation to get to trusted insights within minutes, and integrations with existing databases and tools to simplify setup and user experience.

AI 74

AI AI Machine Learning Machine Learning 74

Alation

JUNE 9, 2021

The explosion in data and database types is a major pain point of the modern data consumer. What is Data Search & Discovery? According to IDC , more than 59 zettabytes (59,000,000,000,000,000,000,000 bytes) of data was created, captured, and consumed in the world in 2020. Today they have too much.

Data Governance 59

Data Governance Database Cloud Data Machine Learning 59

Alation

MARCH 29, 2021

A modern data catalog is more than just a collection of your enterprise’s every data asset. It’s also a repository of metadata — or data about data — on information sources from across the enterprise, including data sets, business intelligence reports, and visualizations.

Machine Learning 59

Machine Learning Machine Learning Data Lakes Hadoop 59

IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. After all, Alex may not be aware of all the data available to her.

Data Quality 52

Data Quality Data Governance Data Scientist Data Wrangling 52

IBM Journey to AI blog

JULY 1, 2024

Extraction, transformation and loading (ETL) tools dominated the data integration scene at the time, used primarily for data warehousing and business intelligence. Data is touched and manipulated by a myriad of solutions, including on-premises and cloud transformation tools, databases and data lake houses.

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ETL Data Lakes Database Data Pipeline 40

Dataversity

DECEMBER 15, 2021

The abilities of an organization towards capturing, storing, and analyzing data; searching, sharing, transferring, visualizing, querying, and updating data; and meeting compliance and regulations are mandatory for any sustainable organization.

Data Warehouse 98

Data Warehouse Data Lakes Database Business Intelligence 98