O'Reilly on Data

FEBRUARY 11, 2020

Just 20% of organizations publish data provenance and data lineage. Adopting AI can help data quality. Almost half (48%) of respondents say they use data analysis, machine learning, or AI tools to address data quality issues. Can AI be a catalyst for improved data quality?

Data Quality 299

Data Quality Metadata Data Governance Publishing 299

Cloudera

MARCH 17, 2023

The one key component that is missing is a common, shared table format, that can be used by all analytic services accessing the lakehouse data. The table format provides the necessary structure for the unstructured data that is missing in a data lake, using a schema or metadata definition, to bring it closer to a data warehouse.

Unstructured Data 62

Unstructured Data Data Lake Data Warehouse Machine Learning 62

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 109

Data Lake Unstructured Data Data Warehouse Data Quality 109

Smart Data Collective

APRIL 5, 2022

They are using tools like Amazon SageMaker to take advantage of more powerful machine learning capabilities. Amazon SageMaker is a hardware accelerator platform that uses cloud-based machine learning technology. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks.

Cost-Benefit 123

Cost-Benefit Machine Learning Data Science Unstructured Data 123

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale.

Data Lake 90

Data Lake Analytics Snapshot Optimization 90

CIO Business Intelligence

OCTOBER 13, 2023

Information/data governance architect: These individuals establish and enforce data governance policies and procedures. Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.

Data Architecture 130

Data Architecture Data Warehouse Statistics Visualization 130

Sisense

AUGUST 21, 2020

AI and machine learning are the future of every industry, especially data and analytics. Reading through the Gartner Top 10 Trends in Data and Analytics for 2020 , I was struck by how different terms mean different things to different audiences under different contexts.

Analytics 112

Analytics Machine Learning Dashboards Visualization 112

Cloudera

SEPTEMBER 9, 2022

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Metadata 100

Metadata Machine Learning Unstructured Data Data Lake 100

Alation

MARCH 21, 2023

Today, modern travel and tourism thrive on data. For example, airlines have historically applied analytics to revenue management, while successful hospitality leaders make data-driven decisions around property allocation and workforce management. What is big data in the travel and tourism industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Ontotext

MAY 22, 2023

Click To Tweet How will LLM impact text analysis and content analytics? This is the case with the so-called intelligent data processing (IDP), which uses a previous generation of machine learning. Back to the mainstream, how does Ontotext help deliver better analytics?

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

Cloudera

SEPTEMBER 15, 2022

Apache Ozone is a distributed, scalable, and high-performance object store , available with Cloudera Data Platform (CDP), that can scale to billions of objects of varying sizes. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. OBJECT_STORE Bucket (“OBS”).

Metadata 87

Metadata Big Data Optimization Unstructured Data 87

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Consulting Enterprise 78

Cloudera

JUNE 7, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 110

IT Data Architecture Unstructured Data Big Data 110

Cloudera

NOVEMBER 17, 2022

While Cloudera CDH was already a success story at HBL, in 2022, HBL identified the need to move its customer data centre environment from Cloudera’s CDH to Cloudera Data Platform (CDP) Private Cloud to accommodate growing volumes of data. and primarily served regulatory reporting and internal analytics requirements.

Management 84

Management Data Lake Consulting Unstructured Data 84

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

JUNE 23, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. Jonathan Takiff / IDG.

IT 83

IT Data Architecture Unstructured Data Big Data 83

IBM Big Data Hub

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. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 62

Data Architecture Data Lake Machine Learning Data Governance 62

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

IBM Big Data Hub

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions. See what’s ahead AI can assist with forecasting.

Cost-Benefit 85

Cost-Benefit Insurance Unstructured Data Machine Learning 85

Alation

NOVEMBER 22, 2022

Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge. Standardizing data formats. Securing Data.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

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. Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently.

Data Lake 92

Data Lake Unstructured Data Management Modeling 92

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Deploying Data Lakes in the cloud. Possibilities with Data Lakes.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

AWS Big Data

AUGUST 15, 2023

As customers accelerate their migrations to the cloud and transform their businesses, some find themselves in situations where they have to manage data analytics in a multi-cloud environment, such as acquiring a company that runs on a different cloud provider. We use Athena to run queries on data stored on Google Cloud Storage.

Recreation/Entertainment 90

Recreation/Entertainment Unstructured Data Business Intelligence Data-driven 90

Alation

DECEMBER 15, 2021

And in the world of analytics, bad data makes for bad decisions. A data governance strategy helps prevent your organization from having “bad data” — and the poor decisions that may result! Organizations need to balance offense and defense, and a robust data governance strategy can help.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

AWS Big Data

FEBRUARY 22, 2023

The data lake implemented by Ruparupa uses Amazon S3 as the storage platform, AWS Database Migration Service (AWS DMS) as the ingestion tool, AWS Glue as the ETL (extract, transform, and load) tool, and QuickSight for analytic dashboards. This long processing time reduced the analytic team’s productivity.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The third challenge is how to combine data management with analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Ontotext

DECEMBER 16, 2020

In its third generation, Ontotext Platform enables organizations to build, use and evolve knowledge graphs as a hub for data, metadata and content. From Data Silos to Data Fabric with Knowledge Graphs. We also continued to improve our knowledge graph platform. Check out Ontotext Platform 3.1 , 3.2 , and 3.3.

Metadata 52

Metadata Unstructured Data Visualization Enterprise 52

Alation

JUNE 2, 2022

In part two of this series, I’ll dive more deeply into AI/ML and data lineage, in the cloud and otherwise, and discuss how data governance and security can support these critical use cases, wherever they reside. Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 115

Data Lake Metadata Optimization Statistics 115

CIO Business Intelligence

MARCH 29, 2022

It isn’t practical to save all your data, but it is important to realize data may be valuable for other projects. You lose that add-on value when you throw data away. . This type of data waste results in missing out on the second project advantage. You have data but don’t use it.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Ontotext

FEBRUARY 26, 2024

Strategic planning and predictive analytics : Companies can use this analysis for strategic planning. Quality assurance process, covering gold standard creation , extraction quality monitoring, measurement, and reporting via Ontotext Metadata Studio. Using machine learning, RED indicates the impact of events on stock prices.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

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 65

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 65

Ontotext

NOVEMBER 22, 2020

Ontotext is also on the list of vendors supporting knowledge graph capabilities in their “2021 Planning Guide for Data Analytics and Artificial Intelligence” report. Content Enrichment and Metadata Management. The value of metadata for content providers is well-established. Data silos are as costly as they are inevitable.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

AWS Big Data

MARCH 10, 2023

Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats. However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. He holds a PhD on data management in the cloud.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

Domino Data Lab

JANUARY 21, 2021

This blog explores the challenges associated with doing such work manually, discusses the benefits of using Pandas Profiling software to automate and standardize the process, and touches on the limitations of such tools in their ability to completely subsume the core tasks required of data science professionals and statistical researchers.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Sisense

MAY 28, 2020

In the Clouds is where we explore the ways cloud-native architecture, cloud data storage, and cloud analytics are changing key industries and business practices, with anecdotes from experts, how-to’s, and more to help your company excel in the cloud era. The world of data is constantly changing and speeding up every day.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 92

Data Processing Data Warehouse Enterprise Visualization 92