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 Models Data Modeling Data Warehouse 52

Dataconomy

MAY 26, 2025

By employing sophisticated statistical models and methodologies, businesses can decode trends, enhance operational efficiency, and gain a competitive edge in an increasingly data-centric landscape. What is business analytics? Foundational processes Establishment of business goals: Defining clear objectives to guide the analysis.

Analytics 91

Analytics Analytics Data Analysis Data Analysis 91

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 132

SQL Data Lakes Data Analyst AWS 132

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

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. 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

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

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

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

Pickl AI

FEBRUARY 23, 2025

Microsoft Azure HDInsight Azure HDInsight is a fully-managed cloud service that makes it easy to process Big Data using popular open-source frameworks such as Hadoop, Spark, and Kafka. Key Features : Integration with Microsoft Services : Seamlessly integrates with other Azure services like Azure Data Lake Storage.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 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. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 94

Data Science Analytics Analytics Data Scientist 94

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

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.

AWS 130

AWS Natural Language Processing Machine Learning Machine Learning 130

Pickl AI

MARCH 10, 2025

Summary: Power BI is a business intelligence tool that transforms raw data into actionable insights. Introduction Managing business and its key verticals can be challenging. Power BI is a powerful business intelligence tool that transforms raw data into actionable insights through interactive dashboards and reports.

Power BI 52

Power BI Business Intelligence Business Intelligence Analytics 52

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. Furthermore, data mining can help organisations better understand their customers.

Data Mining 52

Data Mining Data Mining Data Mining Data Scientist 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.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Alation

SEPTEMBER 23, 2021

What Is a Data Catalog? A data catalog is a centralized storage bank of metadata on information sources from across the enterprise, such as: Datasets. Business intelligence reports. The data catalog also stores metadata (data about data, like a conversation), which gives users context on how to use each asset.

Data Preparation 52

Data Preparation SQL Data Governance Data Analysis 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

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

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

Alation

FEBRUARY 20, 2020

. ; there has to be a business context, and the increasing realization of this context explains the rise of information stewardship applications.” – May 2018 Gartner Market Guide for Information Stewardship Applications. The rise of data lakes, IOT analytics, and big data pipelines has introduced a new world of fast, big data.

Data Governance 52

Data Governance Tableau Analytics Analytics 52

DagsHub

NOVEMBER 11, 2024

These processes are essential in AI-based big data analytics and decision-making. Data Lakes Data lakes are crucial in effectively handling unstructured data for AI applications. They serve as centralized repositories where raw data, whether structured or unstructured, can be stored in its native format.

AI 52

AI AI Data Lakes Database 52

ODSC - Open Data Science

JANUARY 18, 2024

Like with any professional shift, it’s always good practice to take inventory of your existing data science strengths. Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. With that said, each skill may be used in a different manner.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Alation

MARCH 21, 2023

The travel and tourism industry can use predictive, descriptive, and prescriptive analytics to make data-driven decisions that ultimately enhance revenue, mitigate risk, and increase efficiencies. Using Alation, ARC automated the data curation and cataloging process. “So

Analytics 52

Analytics Analytics Data Silos Big Data 52

Smart Data Collective

AUGUST 7, 2019

In 2019, big data technology is paramount in business. Big data is an indispensable product which contains valuable insight necessary in decision-making. The concept of data analysis is, therefore, essential for every organization that deals with vast amounts of data every day. Data management platform.

Analytics 111

Analytics Analytics Big Data Big Data 111