Cloudera

JUNE 7, 2023

It operates independently from compute and storage layers, offering integrated security and governance based on metadata. With persistent context across analytics and cloud environments, SDX simplifies data delivery and access with a unified multi-tenant model. Understanding your data is critical to protecting the data.

Metadata 78

Metadata Data Lake Optimization Modeling 78

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Lack of a solid data governance foundation increases the risk of data-security incidents.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

JANUARY 31, 2023

In addition, data governance is required to comply with an increasingly complex regulatory environment with data privacy (such as GDPR and CCPA) and data residency regulations (such as in the EU, Russia, and China). Sharing data using LF-tags helps scale permissions and reduces the admin work for data lake builders.

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

erwin

SEPTEMBER 3, 2020

You can collect complete application ecosystem information; objectively identify connections/interfaces between applications, using data; provide accurate compliance assessments; and quickly identify security risks and other issues. Automating Data Governance and Enterprise Architecture.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. Figure 1 – Data Catalog Metadata Subjects.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

CIO Business Intelligence

DECEMBER 4, 2023

Beyond “records,” organizations can digitally capture anything and apply metadata for context and searchability. For example, a purpose-built content services platform and well-architected data lake can provide easy access for automation and AI use. Structure/Operationalize. Preserve/Dispose.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

Ontotext

FEBRUARY 12, 2024

It’s also critical to advocate a smooth culture change because data mesh involves shifting from thinking about data as tables to data as a combination of multiple elements, such as code, infrastructure, and metadata. Each team should be accountable for providing their prepared data sets to downstream systems.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

AWS Big Data

MARCH 27, 2023

Developers, data scientists, and analysts can work across databases, data warehouses, and data lakes to build reporting and dashboarding applications, perform real-time analytics, share and collaborate on data, and even build and train machine learning (ML) models with Redshift Serverless.

Data Warehouse 81

Data Warehouse Management Snapshot Data Lake 81

AWS Big Data

NOVEMBER 17, 2023

Athena provides a simplified, flexible way to analyze petabytes of data where it lives. You can analyze data or build applications from an Amazon Simple Storage Service (Amazon S3) data lake and 30 data sources, including on-premises data sources or other cloud systems using SQL or Python.

Optimization 108

Optimization Statistics Metadata Data Lake 108

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Technical metadata to describe schemas, indexes and other database objects.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

Data-driven 59

Data-driven Enterprise Data Governance Data Lake 59

Alation

MARCH 22, 2022

So, how can you quickly take advantage of the DataOps opportunity while avoiding the risk and costs of DIY? More specifically, IDF has been integrated with Alation at an API level; this means that all generated pipeline code, metadata attributes, configuration files, and lineage are automatically synced (representing a huge time savings).

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake.

Data Lake 78

Data Lake Data Architecture Data-driven Data Warehouse 78

Alation

APRIL 18, 2023

Gartner defines data profiling as: A technology for discovering and investigating data quality issues, such as duplication, lack of consistency, and lack of accuracy and completeness. The tools provide data statistics, such as degree of duplication and ratios of attribute values, both in tabular and graphical formats.

IT 52

IT Data Quality Metadata Data Governance 52

CIO Business Intelligence

SEPTEMBER 6, 2022

But getting to this stage was an intricate process that involved creating centers of excellence for things like data analytics that own the end-to-end infrastructure, application and skill sets, as well as career plans for staff. Understanding what data you’ve got locked in all these different stores is a big part of the jigsaw puzzle.”.

IT 98

IT Forecasting Data Lake Enterprise 98

Cloudera

MAY 12, 2021

We welcome organizations that have built and deployed use cases for enterprise-scale machine learning and have industrialized AI to automate, secure, and optimize data-driven decision-making and/or applications to enter this category. Read more about last years Data Impact Award winners. HYBRID & MULTI-CLOUD INNOVATION.

Digital Transformation 65

Digital Transformation Machine Learning Optimization Data Lake 65

bridgei2i

MARCH 11, 2021

From eliminating the need for human assistance in repetitive tasks to reducing the risk of human errors in manual processes – AI can do a lot for large-scale businesses. With improved data cataloging functionality, their systems can become responsive. Not if they get started now! in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Cloudera

NOVEMBER 12, 2020

Cloud has given us hope, with public clouds at our disposal we now have virtually infinite resources, but they come at a different cost – using the cloud means we may be creating yet another series of silos, which also creates unmeasurable new risks in security and traceability of our data. Key areas of concern are: .

Data Warehouse 101

Data Warehouse Reporting Risk Cost-Benefit 101

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Alation

JUNE 14, 2021

Do we know the business outcomes tied to data risk management? Once you have data classification then you can talk about whether you need to tokenize and why, or anonymize and why, or encrypt and why, etc.” Indeed, automation is a key element to data catalog features, which enhance data security. What do we know?

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

Alation

NOVEMBER 28, 2022

If unaddressed, this chaos can lead to data quality, compliance, and security issues. Any spreadsheet platform poses risks. Most enterprise data users use Excel today to make business decisions. But refreshing this analysis with the latest data was impossible… unless you were proficient in SQL or Python.

Metadata 52

Metadata Enterprise Cost-Benefit Finance 52

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. Why did Orca build a data lake?

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

FEBRUARY 13, 2020

MunichRe’s data catalog sped the introduction of new, innovative data products to mitigate the risk of high impact crises caused by global warming. The Alation Data Catalog is taking years of data lake and self-service analytics investments and driving them from investments to insights.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

In(tegrate) the Clouds

DECEMBER 21, 2015

Aside from the Internet of Things, which of the following software areas will experience the most change in 2016 – big data solutions, analytics, security, customer success/experience, sales & marketing approach or something else? 2016 will be the year of the data lake. What are the biggest risks for software buyers in 2016?

Technology 45

Technology Internet of Things Digital Transformation Software 45

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 95

Data Lake Data Warehouse Management Risk 95

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models. earthquake, flood, or fire), where the data collected does not need to be as tightly controlled.

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

AWS Big Data

NOVEMBER 29, 2023

With Redshift, we are able to view risk counterparts and data in near real time— instead of on an hourly basis. Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

AWS Big Data

JULY 3, 2023

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance.

Snapshot 80

Snapshot Data Lake Testing Strategy 80

Alation

APRIL 6, 2023

Other forms of governance address specific sets or domains of data including information governance (for unstructured data), metadata governance (for data documentation), and domain-specific data (master, customer, product, etc.). Data catalogs and spreadsheets are related in many ways.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

Cloudera

JANUARY 21, 2021

And you also already know siloed data is costly, as that means it will be much tougher to derive novel insights from all of your data by joining data sets. Of course you don’t want to re-create the risks and costs of data silos your organization has spent the last decade trying to eliminate. Must you be: .

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. 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. Warehouse, data lake convergence. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

AWS Big Data

JULY 28, 2023

Data dependencies – Personal data can be interconnected and intertwined with other data systems, making it challenging to remove specific data without impacting the integrity of functionality of other systems or processes. Ensuring the complete removal of data from all these copies and backups can be challenging.

Snapshot 79

Snapshot Metadata Measurement Data Warehouse 79