Cloudera

OCTOBER 5, 2023

Your organization is not alone — many organizations struggle to move towards data as the cornerstone of their organization. Here are five challenges that you need to overcome to become a data leader: Bad data governance Your insights are only as good as your data.

Data-driven 87

Data-driven Enterprise Data Governance Unstructured Data 87

O'Reilly on Data

FEBRUARY 11, 2020

They have too many different data sources and too much inconsistent data. They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. Nearly one-quarter of respondents work as data scientists or analysts (see Figure 1).

Data Quality 299

Data Quality Metadata Data Governance Publishing 299

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. . Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs.

Testing 300

Testing Machine Learning Consulting Data Quality 300

IBM Big Data Hub

JANUARY 17, 2023

Essential components of a data lakehouse architecture and what makes an open data lakehouse. At the core of a data lakehouse architecture includes the storage, metadata service and the query engine, and typically a data governance component made up of a policy engine and a data dictionary.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Cloudera

NOVEMBER 18, 2021

By adopting a custom developed application based on the Cloudera ecosystem, Carrefour has combined the legacy systems into one platform which provides access to customer data in a single data lake. In doing so, Bank of the West has modernized and centralized its Big Data platform in just one year.

Data Lake 80

Data Lake Cost-Benefit Digital Transformation Risk 80

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. The approach they’ve used applies to other popular data science APIs such as NumPy , Tensorflow , and so on.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CIO Business Intelligence

MAY 24, 2022

Today transactional data is the largest segment, which includes streaming and data flows. EXTRACTING VALUE FROM DATA. One of the biggest challenges presented by having massive volumes of disparate unstructured data is extracting useable information and insights.

Data-driven 98

Data-driven Data Lake Data Warehouse Cost-Benefit 98

Grooper

AUGUST 19, 2019

Applied analytics Business analytics Machine learning and data science. Think of applied analytics as specific use cases for your industry that identify the exact insights and data that would create the best outcomes in specific business processes. Master data management. Data governance. Data pipelines.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Alation

DECEMBER 15, 2021

Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information. Data governance requires a system.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

CIO Business Intelligence

AUGUST 1, 2023

But with all the excitement and hype, it’s easy for employees to invest time in AI tools that compromise confidential data or for managers to select shadow AI tools that haven’t been through security, data governance, and other vendor compliance reviews.

Digital Transformation 98

Digital Transformation Unstructured Data Strategy Experimentation 98

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Datasphere manages and integrates structured, semi-structured, and unstructured data types.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325