Flipboard

MAY 20, 2025

Enterprisesespecially in the insurance industryface increasing challenges in processing vast amounts of unstructured data from diverse formats, including PDFs, spreadsheets, images, videos, and audio files. All contain critical information across the claims processing lifecycle.

Data Lakes 124

Data Lakes AWS Analytics Analytics 124

Dataconomy

JUNE 18, 2025

Data integration is an essential aspect of modern businesses, enabling organizations to harness diverse information sources to drive insights and decision-making. In today’s data-driven world, the ability to combine data from various systems and formats into a unified view is paramount.

Data Warehouse 91

Data Warehouse Data Silos ETL Big Data 91

Flipboard

MAY 14, 2025

In this post, we show you how Amazon Q Business can help augment your generative AI needs in all the abovementioned use cases and more by answering questions, providing summaries, generating content, and securely completing tasks based on data and information in your enterprise systems.

AWS 139

AWS AI AI Database 139

Flipboard

APRIL 17, 2023

Enterprises often rely on data warehouses and data lakes to handle big data for various purposes, from business intelligence to data science. A new approach, called a data lakehouse, aims to …

Data Lakes 123

Data Lakes Data Warehouse Big Data Big Data 123

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 337

Power BI Data Pipeline Data Warehouse Data Engineering 337

Pickl AI

JANUARY 28, 2025

Summary: Understanding Business Intelligence Architecture is essential for organizations seeking to harness data effectively. This framework includes components like data sources, integration, storage, analysis, visualization, and information delivery. What is Business Intelligence Architecture?

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

AWS Machine Learning Blog

AUGUST 8, 2024

Data is the foundational layer for all generative AI and ML applications. Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries. The following diagram illustrates the solution architecture.

SQL 126

SQL Data Lakes Data Analyst AWS 126

Dataconomy

FEBRUARY 26, 2025

Data mining has emerged as a vital tool in todays data-driven environment, enabling organizations to extract valuable insights from vast amounts of information. As businesses generate and collect more data than ever before, understanding how to uncover patterns and trends becomes essential for making informed decisions.

Data Mining 91

Data Mining Data Mining Data Mining Data Preparation 91

phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

AWS Machine Learning Blog

DECEMBER 3, 2024

Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. AWS IAM Identity Center set up to be used with Amazon Q Business. For more information, see Creating a topic.

AWS 99

AWS Database Data Silos Data Lakes 99

AWS Machine Learning Blog

NOVEMBER 14, 2024

When defining your tagging strategy, you need to determine the right tags that will gather all the necessary information in your environment. Avoid personally identifiable information (PII) when labeling resources because tags remain unencrypted and visible. This identifies teams or cost centers responsible for those resources.

ML 108

ML ML AWS Machine Learning 108

Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. It will enable you to quickly transform and load the data results into Amazon S3 data lakes or JDBC data stores.

Apache Kafka 130

Apache Kafka ETL Data Lakes AWS 130

AWS Machine Learning Blog

APRIL 3, 2025

Data is one of the most critical assets of many organizations. Theyre constantly seeking ways to use their vast amounts of information to gain competitive advantages. Amazon AppFlow was used to facilitate the smooth and secure transfer of data from various sources into ODAP.

AWS 81

AWS Data Governance Data Silos SQL 81

Dataconomy

MARCH 4, 2025

This article delves into the essential components of data mining, highlighting its processes, techniques, tools, and applications. What is data mining? Data mining refers to the systematic process of analyzing large datasets to uncover hidden patterns and relationships that inform and address business challenges.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

Dataconomy

SEPTEMBER 4, 2023

Cloud analytics is the art and science of mining insights from data stored in cloud-based platforms. By tapping into the power of cloud technology, organizations can efficiently analyze large datasets, uncover hidden patterns, predict future trends, and make informed decisions to drive their businesses forward.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

NOVEMBER 9, 2023

The main goal of a data mesh structure is to drive: Domain-driven ownership Data as a product Self-service infrastructure Federated governance One of the primary challenges that organizations face is data governance. What is a Data Lake? What is the Difference Between a Data Lake and a Data Warehouse?

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98

Dataconomy

MAY 26, 2025

Business analytics is a powerful enabler for organizations seeking to harness the quintessence of information to optimize performance and drive strategic initiatives. It delves beyond mere data collection, engaging in the processes of extracting meaningful insights to inform better business decisions.

Analytics 91

Analytics Analytics Data Analysis Data Analysis 91

Dataconomy

NOVEMBER 19, 2024

Many companies are making a business out of helping enterprises get data out of old systems, and tools like Apache Airflow are helping streamline these processes. But even if data is no longer stuck in mainframes, it’s still fragmented across systems like cloud SaaS services or data lakes.

AI 113

AI AI Business Intelligence Business Intelligence 113

Dataversity

NOVEMBER 10, 2022

There are several reasons why the notion of semantic layers has reached the forefront of today’s data management conversations. The analyst community is championing the data fabric tenet. The data mesh and data lake house architectures are gaining traction. Data lakes are widely deployed.

Data Lakes 52

Data Lakes Business Intelligence Business Intelligence 52

ODSC - Open Data Science

FEBRUARY 24, 2023

Data Quality Now that you’ve learned more about your data and cleaned it up, it’s time to ensure the quality of your data is up to par. With these data exploration tools, you can determine if your data is accurate, consistent, and reliable.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Flipboard

MAY 9, 2025

Our solution integrates sentiment analysis, content generation, and campaign effectiveness prediction into a unified architecture, allowing for more informed marketing decisions. This pattern creates a comprehensive solution that transforms raw social media data into actionable business intelligence (BI) through advanced AI capabilities.

AWS 91

AWS Natural Language Processing AI AI 91

Pickl AI

FEBRUARY 23, 2025

Introduction to Big Data Tools In todays data-driven world, organisations are inundated with vast amounts of information generated from various sources, including social media, IoT devices, transactions, and more. Big Data tools are essential for effectively managing and analysing this wealth of information.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

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

Pickl AI

DECEMBER 2, 2024

This explosive growth of data is driven by various factors, including the proliferation of internet-connected devices, social media interactions, and the increasing digitization of business processes. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

This explosive growth of data is driven by various factors, including the proliferation of internet-connected devices, social media interactions, and the increasing digitization of business processes. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Dataversity

JANUARY 25, 2023

Over the past few years, enterprise data architectures have evolved significantly to accommodate the changing data requirements of modern businesses. Data warehouses were first introduced in the […] The post Are Data Warehouses Still Relevant?

Data Warehouse 52

Data Warehouse Data Lakes Cloud Computing Data Pipeline 52

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. For more information, refer to Prompt engineering.

AWS 126

AWS Natural Language Processing Machine Learning Machine Learning 126

IBM Journey to AI blog

AUGUST 4, 2023

Architecture for data democratization Data democratization requires a move away from traditional “data at rest” architecture, which is meant for storing static data. Traditionally, data was seen as information to be put on reserve, only called upon during customer interactions or executing a program.

Data Lakes 73

Data Lakes AI AI Data Governance 73

Tableau

DECEMBER 7, 2022

Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. As a result, making informed business decisions was frustrating and time consuming. . Cut costs by consolidating data warehouse investments.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Tableau

DECEMBER 7, 2022

Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. As a result, making informed business decisions was frustrating and time consuming. . Cut costs by consolidating data warehouse investments.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Women in Big Data

NOVEMBER 27, 2024

By maintaining historical data from disparate locations, a data warehouse creates a foundation for trend analysis and strategic decision-making. How to Choose a Data Warehouse for Your Big Data Choosing a data warehouse for big data storage necessitates a thorough assessment of your unique requirements.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

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. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 94

Data Science Analytics Analytics Data Scientist 94

AWS Machine Learning Blog

NOVEMBER 15, 2023

Content redaction: Each customer audio interaction is recorded as a stereo WAV file, but could potentially include sensitive information such as HIPAA-protected and personally identifiable information (PII). PCA’s security features ensure that any PII data was redacted from the transcript, as well as from the audio file itself.

AWS 117

AWS Analytics Analytics ML 117

Alation

FEBRUARY 20, 2020

Organizations who are so successful in their adoption of self-service analytics, that their own business intelligence (BI) evangelists worry that they’ve created an analytics “wild west.” When they see a data catalog for the first time, they’re thrilled that a product exists that can govern the west and increase analyst productivity.

Data Lakes 52

Data Lakes Analytics Analytics Business Intelligence 52

IBM Journey to AI blog

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

AI 93

AI AI Data Scientist Data Governance 93

IBM Journey to AI blog

DECEMBER 7, 2023

OLAP database systems have evolved from specialized analytical tools into comprehensive data analytics platforms, empowering businesses to make informed decisions based on insights from large and complex datasets. IBM watsonx.data is the next generation OLAP system that can help you make the most of your data.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72