Alation

AUGUST 30, 2022

Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. We had data but no data intelligence and, as a result, insights remained hidden or hard to come by. This universe of metadata represents a treasure trove of connected information.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 52

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

erwin

JANUARY 30, 2020

The 2020 State of Data Governance and Automation (DGA) report is a follow-up to an initial survey we commissioned two years ago to explore data governance ahead of the European Union’s General Data Protection Regulation (GDPR) going into effect. 1 reason to implement data governance.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

DataKitchen

AUGUST 3, 2021

Third-generation – more or less like the previous generation but with streaming data, cloud, machine learning and other (fill-in-the-blank) fancy tools. It’s no fun working in data analytics/science when you are the bottleneck in your company’s business processes. Easy to report problems and receive updates on fixes.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

NOVEMBER 22, 2022

“Unique insights derived from an organization’s data constitute a competitive advantage that’s inherent to their business and not easily copied by competitors,” she observes. Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

MARCH 4, 2024

As data volumes continue to increase alongside a correlating number of business requests, modern insurance data leaders face a nuanced set of challenges. Accelerated demand in AI-enabled innovations has recently compounded these issues, prioritizing the need for new capabilities that require even more robust data foundations.

Insurance 87

Insurance Strategy Data Governance Data Integration 87

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? As you can tell, data governance is a hot topic but an area that many public cloud vendors are weak in. You can view the entire research report here (requires Gartner subscription). This is the focus of my latest research which published in Jan 2019.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

Alation

OCTOBER 5, 2021

Yet, so many companies today are still failing miserably in implementing data strategy and governance protocols. Why is your data governance strategy failing? However, about 50% of those surveyed also admit that they do not assess, monitor, or measure their data governance systems. Data governance and AI.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

IBM Big Data Hub

JUNE 8, 2022

However, a foundational step in evolving into a data-driven organization requires trusted, readily available, and easily accessible data for users within the organization; thus, an effective data governance program is key. Here are a few common data management challenges: Regulatory compliance on data use.

Data-driven 56

Data-driven Enterprise Data Governance Data Lake 56

Ontotext

NOVEMBER 18, 2021

Picture this – you start with the perfect use case for your data analytics product. And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own.

Visualization 98

Visualization Reporting Metadata Enterprise 98

Ontotext

JANUARY 26, 2023

” To do so, KWG draws from over 30 fully integrated and semantically homogenized data layers. This number is expected to grow beyond 20B by next year, as reported by the authors of the project. The catalog stores the asset’s metadata in RDF. As a result of these data quality issues, the need for integrity checks arises.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

CIO Business Intelligence

MARCH 29, 2022

A common data habit that results in missed opportunity is assuming data has no further value once it’s been used for the particular purpose. Data is ingested, processed, transformed (perhaps for a specific report or to be stored in a traditional database), and then the raw or partially processed data is discarded.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

AWS Big Data

JUNE 6, 2023

In order to mature our data marts, it became clear that we needed to provide Analysts and other data consumers with all tracked digital analytics data in our DWH as they depend on it for analyses, reporting, campaign evaluation, product development and A/B testing.

Analytics 55

Analytics Data Lake Testing Optimization 55

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. How is data analytics used in the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

DataKitchen

OCTOBER 11, 2021

The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel. Adding Tests to Reduce Stress.

Testing 152

Testing Metadata Dashboards Statistics 152

erwin

FEBRUARY 4, 2021

So what’s holding organizations back from fully using their data to make better, smarter business decisions? Data Governance Bottlenecks. The report revealed that all but two of the possible bottlenecks were marked by more than 50 percent of respondents. Overcoming Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

DECEMBER 18, 2023

There are multiple tables related to customers and order data in the RDS database. Amazon S3 hosts the metadata of all the tables as a.csv file. Handle failures with distributed map By default, when a state reports an error, Step Functions causes the workflow to fail. In his spare time, he enjoys playing Tennis.

Metadata 122

Metadata Visualization Data Lake Data-driven 122

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 105

Data Lake Unstructured Data Data Warehouse Data Quality 105

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.)

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage. With Netezza support for 1.2

Cost-Benefit 76

Cost-Benefit Metadata Optimization Management 76

AWS Big Data

JULY 20, 2023

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

Andrew White

JANUARY 9, 2022

First, how we measure emissions and carbon footprint is about data design and policy. For example I would argue that most organizations that report their carbon footrest are not doing it consistently and nor are they doing it correctly. What is the difference in your view between Data Analytics and Data Science?

Analytics 64

Analytics Measurement Modeling Data-driven 64

Domino Data Lab

JULY 21, 2019

The approach is to provide remote access for government analysts and researchers to confidential data in a secure data facility and to build analytical capacity and collaborations through an Applied Data Analytics training program. But you also need to have metadata around the data. Transcript.

Metadata 65

Metadata Statistics Risk Machine Learning 65

DataKitchen

AUGUST 8, 2023

On 20 July 2023, Gartner released the article “ Innovation Insight: Data Observability Enables Proactive Data Quality ” by Melody Chien. It alerts data and analytics leaders to issues with their data before they multiply. It alerts data and analytics leaders to issues with their data before they multiply.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

datapine

JANUARY 31, 2022

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. Let’s look at our first use case.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Smart Data Collective

OCTOBER 13, 2021

If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future. There is little use for data analytics without the right visualization tool.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Andrew White

JANUARY 11, 2021

What is unique about the D&A Leadership Vision is that it crossed over into business since for many organizations, the CDO reports into the CEO or COO (as examples). The fill report is here: Leadership Vision for 2021: Data and Analytics. CAO, and even where the CAO reports into a different organization.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data lineage is static and often lags by weeks or months.

Testing 130

Testing Data Governance Data Quality Data-driven 130

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 59

Data Architecture Data Lake Machine Learning Data Governance 59

BI-Survey

FEBRUARY 6, 2020

Modernizing and optimizing enterprise reporting – or classical BI – has not been such a priority for many of today’s organizations, even though it constitutes the backbone of information supply for decision support. Technological innovations and their increasing proliferation are shaping enterprise reporting and BI.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

Cloudera

APRIL 1, 2024

This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management. Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics.

Unstructured Data 108

Unstructured Data Cost-Benefit Metadata Machine Learning 108

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. Data and analytics (and maybe AI) are getting very tired terms.

Analytics 68

Analytics Metadata Data Governance Management 68