CIO Business Intelligence

MAY 8, 2024

Of late, innovative data integration tools are revolutionising how organisations approach data management, unlocking new opportunities for growth, efficiency, and strategic decision-making by leveraging technical advancements in Artificial Intelligence, Machine Learning, and Natural Language Processing.

Data Integration 73

Data Integration IoT Cost-Benefit Data Quality 73

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

Data Quality 311

Data Quality Metadata Data Governance Publishing 311

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. The offensive side? The company’s Findability.ai

Unstructured Data 100

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 100

CIO Business Intelligence

NOVEMBER 28, 2023

With organizations seeking to become more data-driven with business decisions, IT leaders must devise data strategies gear toward creating value from data no matter where — or in what form — it resides. Unstructured data resources can be extremely valuable for gaining business insights and solving problems.

Unstructured Data 120

Unstructured Data Data-driven Visualization Data Quality 120

Ontotext

MARCH 20, 2024

Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

CIO Business Intelligence

JUNE 7, 2022

But only in recent years, with the growth of the web, cloud computing, hyperscale data centers, machine learning, neural networks, deep learning, and powerful servers with blazing fast processors, has it been possible for NLP algorithms to thrive in business environments. NLP will account for $35.1 Putting NLP to Work.

Unstructured Data 82

Unstructured Data Deep Learning Insurance Interactive 82

Ontotext

MAY 22, 2023

This is the case with the so-called intelligent data processing (IDP), which uses a previous generation of machine learning. Doug Kimball : Using our knowledge graph, you can develop more complex analytics, such as data mining, Natural Language Processing (NLP) and Machine Learning (ML).

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

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

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. Numbers are only good if the data quality is good.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

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. To overcome these issues, Orca decided to build a data lake.

Data Lake 87

Data Lake Analytics Snapshot Optimization 87

datapine

AUGUST 14, 2019

Geet our bite-sized free summary and start building your data skills! What Is A Data Science Tool? In the past, data scientists had to rely on powerful computers to manage large volumes of data. Our Top Data Science Tools. offers many statistics and machine learning abilities. Source: RStudio.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Alation

JUNE 2, 2022

A data catalog is a central hub for XAI and understanding data and related models. While “operational exhaust” arrived primarily as structured data, today’s corpus of data can include so-called unstructured data. Machine Learning Technology. Other Technologies. Conclusion.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are responsible for developing, testing, and maintaining data pipelines and data architectures. Data scientists use data science to discover insights from massive amounts of structured and unstructured data to shape or meet specific business needs and goals.

Analytics 119

Analytics Data Science Statistics Unstructured Data 119

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. Ontotext Knowledge Graph Platform.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

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. An even larger issue is that people may not know how to see value in data.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Ontotext

DECEMBER 1, 2023

He outlined the challenges of working effectively with AI and machine learning, where knowledge graphs are a differentiator. According to him, “failing to ensure data quality in capturing and structuring knowledge, turns any knowledge graph into a piece of abstract art”.

Metadata 78

Metadata Sales Consulting Enterprise 78

CIO Business Intelligence

SEPTEMBER 2, 2022

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Business analyst.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Business analyst.

Finance 98

Finance IT Software Reporting 98

Jedox

OCTOBER 22, 2020

In addition to using data to inform your future decisions, you can also use current data to make immediate decisions. Some of the technologies that make modern data analytics so much more powerful than they used t be include data management, data mining, predictive analytics, machine learning and artificial intelligence.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Grooper

AUGUST 19, 2019

Applied analytics Business analytics Machine learning and data science. Master data management. Data governance. Structured, semi-structured, and unstructured data. Data pipelines. Enterprise management and use of analytical tools, data, and data science capabilities. Algorithms.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 300

Testing Machine Learning Consulting Data Quality 300

FineReport

APRIL 26, 2023

Recently, Spark set a new record by processing 100 terabytes of data in just 23 minutes, surpassing Hadoop’s previous world record of 71 minutes. This is why big tech companies are switching to Spark as it is highly suitable for machine learning and artificial intelligence. Accomplishes the speed and scale of Spark.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Cloudera

MAY 14, 2024

More than that, though, harnessing the potential of these technologies requires quality data—without it, the output from an AI implementation can end up inefficient or wholly inaccurate. Data comes in many forms. True’ hybrid incorporates data stores that are capable of maintaining and harnessing data, no matter the format.

Data Architecture 99

Data Architecture Data Governance Unstructured Data Structured Data 99

CIO Business Intelligence

MARCH 9, 2022

Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio. They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics.

Data Lake 99

Data Lake Unstructured Data Data Warehouse Data Quality 99

Timo Elliott

JANUARY 22, 2019

Machine learning everywhere. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s. Augmented analytics platforms based on cloud technology and machine learning are breaking down the longest-standing barriers to analytics success.

Analytics 96

Analytics Machine Learning Unstructured Data Digital Transformation 96

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 102

Metadata Machine Learning Unstructured Data Data Lake 102

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

CIO Business Intelligence

JANUARY 20, 2023

Modern compute infrastructures are designed to enhance business agility and time to market by supporting workloads for databases and analytics, AI and machine learning (ML), high performance computing (HPC) and more. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Analytics 125

Analytics Key Performance Indicator Unstructured Data IoT 125

Alation

AUGUST 4, 2022

Many CIOs argue the rise of big data pushed people to use data more proactively for business decision-making. Big data got“ more leaders and people in the organization to use data, analytics, and machine learning in their decision making,” says former CIO Isaac Sacolick.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

Alation

DECEMBER 15, 2021

A data governance strategy helps prevent your organization from having “bad data” — and the poor decisions that may result! Here’s why organizations need a governance strategy: Makes data available: So people can easily find and use both structured and unstructured data. Measure data usage.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

IBM Big Data Hub

AUGUST 4, 2023

Data within a data fabric is defined using metadata and may be stored in a data lake, a low-cost storage environment that houses large stores of structured, semi-structured and unstructured data for business analytics, machine learning and other broad applications.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

datapine

DECEMBER 4, 2019

Considered a new big buzz in the computing and BI industry, it enables the digestion of massive volumes of structured and unstructured data that transform into manageable content. It is the combination of several data processes that, instead of just giving back data, but provides a valuable, strategy-changing recommendation.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? 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.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Jet Global

MAY 9, 2024

Data Migration Pipelines : These pipelines move data from one system to another, often for the purpose of upgrading systems or consolidating data sources. For example, migrating customer data from an on-premises database to a cloud-based CRM system. structured, semi-structured, or unstructured data).

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52