IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. However, the value of such important data diminishes significantly over time.

Data Lake 89

Data Lake Unstructured Data Management Modeling 89

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. “It The company’s Findability.ai

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

CIO Business Intelligence

DECEMBER 4, 2023

Tomorrow’s market leaders will recognize how to curate and enrich the value of all assets, which will train AI models, generate insights, and drive automation. The ways modern data is used, processed, and analyzed are continuously evolving as machine learning technology becomes better at these tasks. Connect/Activate.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

CIO Business Intelligence

OCTOBER 25, 2023

The release of intellectual property and non-public information Generative AI tools can make it easy for well-meaning users to leak sensitive and confidential data. Once shared, this data can be fed into the data lakes used to train large language models (LLMs) and can be discovered by other users.

Enterprise 133

Enterprise Risk Manufacturing Finance 133

IBM Big Data Hub

APRIL 25, 2023

Relational databases were adapted to accommodate the demands of new workloads, such as the data engineering tasks associated with structured and semi-structured data, and for building machine learning models. To effectively use raw data, it often needs to be curated within a data warehouse.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

IBM Big Data Hub

JULY 5, 2022

Empower real-time decision making and perform heavy computational analysis with built-in ML, insanely fast ingest, and querying of data in motion and at rest. Real-time warehousing with continual data ingestion, so analysts can enjoy low-latency analytics . Vektis improves healthcare quality through data .

Data Lake 96

Data Lake Data Warehouse Publishing Structured Data 96

Sisense

APRIL 26, 2020

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Cost Cloud services operate on a pay-as-you-go model, and estimating costs accurately can be challenging during a POC.

Testing 99

Testing Data Warehouse Metrics Cost-Benefit 99

BizAcuity

MARCH 1, 2019

Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. This is where AI-based analysis and response play a critical role in extracting optimal value from the data. Bringing the power of AI to IoT.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

AWS Big Data

MARCH 27, 2024

Amazon Redshift integrates with AWS HealthLake and data lakes through Redshift Spectrum and Amazon S3 auto-copy features, enabling you to query data directly from files on Amazon S3. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Analytics 90

Data Analytics Analytics Data Warehouse Data Lake 90

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. This will make the data more trustworthy and reliable.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Alation

MAY 16, 2023

Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Ingestion tools are connected to various data sources.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

AWS Big Data

APRIL 19, 2023

Building an optimal data system As data grows at an extraordinary rate, data proliferation across your data stores, data warehouse, and data lakes can become a challenge. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

Unstructured Data 118

Unstructured Data Metadata Management Analytics 118

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Alation

MAY 16, 2023

Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Ingestion tools are connected to various data sources.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

AWS Big Data

MARCH 26, 2024

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. Unified customer profile Graph databases excel in modeling customer interactions and relationships, offering a comprehensive view of the customer journey.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

Corinium

APRIL 25, 2019

Then you can be more confident you’re protecting that data in the right way, in the right places, via protection policies that keep it safe without getting in the way of the business getting value from that data. In data-driven organizations, data is flowing. The protection policy follows the data.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Sisense

JULY 22, 2020

The trend has been towards using cloud-based applications and tools for different functions, such as Salesforce for sales, Marketo for marketing automation, and large-scale data storage like AWS or data lakes such as Amazon S3 , Hadoop and Microsoft Azure. Sisense provides instant access to your cloud data warehouses.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Sisense

JUNE 30, 2020

When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations. Visua l analytics does the “heavy lifting” with data, by using a variety of processes — mechanical, algorithms, machine learning , natural language processing, etc — to identify and reveal patterns and trends.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

AWS Big Data

JUNE 21, 2023

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). In this post, we walk through the process of exporting data from a DynamoDB table to Amazon Redshift. We discuss data model design for both NoSQL databases and SQL data warehouses.

Data Warehouse 79

Data Warehouse Data Lake OLAP Cost-Benefit 79

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. You can use simple SQL to analyze structured and semi-structured data, operational databases, and data lakes to deliver the best price/performance at any scale.

Big Data 66

Big Data Data Warehouse Advertising OLAP 66

CIO Business Intelligence

MARCH 6, 2023

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

Data Lake 88

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 88