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. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

JUNE 8, 2022

By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage. Ensuring data quality and access within an organization, while establishing and maintaining proper governance processes, is a major struggle for many organizations.

Data-driven 59

Data-driven Enterprise Data Governance Data Lake 59

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. What is a data fabric?

Data Lake 81

Data Lake Data Architecture Data-driven Data Warehouse 81

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 103

Data Warehouse Reporting Risk Cost-Benefit 103

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. SECURITY AND GOVERNANCE LEADERSHIP. Read more about last years Data Impact Award winners.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

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. This is especially helpful when handling massive amounts of big data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56

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

Ontotext

MARCH 8, 2023

Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. A risk issue in one financial institution could result in a domino effect for many. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. Spreadsheets are not typically developed and managed for enterprise use, which opens the door to risk from malicious actors, as well as human errors.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 94

Data Analytics Analytics Data Warehouse Data Lake 94

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Humans can’t keep up.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

CIO Business Intelligence

SEPTEMBER 21, 2022

CMOs need to look for ways to leverage customer data to deliver superior and highly tailored experiences to customers. CIOs need to ensure that the business’ use of data is compliant, secure, and done according to best practices. They need to assure the board that the risk from data is minimised.

Risk 105

Risk Data Lake Marketing Interactive 105

BizAcuity

APRIL 14, 2022

Be it supply chain resilience, staff management, trend identification, budget planning, risk and fraud management, big data increases efficiency by making data-driven predictions and forecasts. With adequate market intelligence, big data analytics can be used for unearthing scope for product improvement or innovation.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Enrichment typically involves adding demographic, behavioral, and geolocation data.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

IBM Big Data Hub

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. And that makes sense.

Cost-Benefit 85

Cost-Benefit Metadata Data Governance Modeling 85

Alation

MARCH 1, 2022

Lineage helps them identify the source of bad data to fix the problem fast. Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC.

Data Warehouse 52

Data Warehouse Data Lake Risk Data-driven 52

IBM Big Data Hub

MARCH 14, 2024

By using decades of database expertise in performance by IBM and combining it with AWS’s scalability, security and governance features, customers can achieve enhanced flexibility, agility and cost efficiency in the cloud. This integration simplifies data management and accelerates the preparation process, directly benefiting clients.

Cost-Benefit 85

Cost-Benefit Metadata Optimization Management 85

AWS Big Data

JULY 28, 2023

Organizations must comply with these requests provided that there are no legitimate grounds for retaining the personal data, such as legal obligations or contractual requirements. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. The AWS DPA is incorporated into the AWS Service Terms.

Snapshot 84

Snapshot Metadata Measurement Data Warehouse 84

erwin

JANUARY 10, 2024

The result is an improvement in quality and availability of data such that you can monetize it. Your goal should be enterprise data management and an analytics function that pays for itself, like a self-funding data warehouse, data lake or data mesh. What is data monetization?

Measurement 59

Measurement Cost-Benefit Data Governance Management 59

AWS Big Data

FEBRUARY 27, 2024

The following are the key components of the Bluestone Data Platform: Data mesh architecture – Bluestone adopted a data mesh architecture, a paradigm that distributes data ownership across different business units. This enables data-driven decision-making across the organization.

Data-driven 97

Data-driven Data Lake Data Quality Data Governance 97

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 66

Data Architecture Data Lake Machine Learning Data Governance 66

Alation

JANUARY 27, 2022

People might not understand the data, the data they chose might not be ideal for their application, or there might be better, more current, or more accurate data available. An effective data governance program ensures data consistency and trustworthiness. It can also help prevent data misuse.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 92

Data Lake Data Warehouse Data-driven B2B 92

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. The solution is data intelligence. It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Alation

APRIL 19, 2022

Further, data modernization reduces data security and privacy compliance risks. Its process includes identifying sensitive information so you can limit users’ access to data precisely and efficiently. In that sense, data modernization is synonymous with cloud migration. How to Modernize Data with Alation.

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52

Andrew White

JANUARY 11, 2021

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Governance. Link Data to Business Outcomes.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Andrew White

MARCH 22, 2019

This ties into the failure of data governance and MDM (see first item in this list). A data hub strategy should be economical, not perfected; and a data hub does not collect data like a data warehouses or data lake does – they are very different things. Age maybe against us.

Analytics 68

Analytics Metadata Data Governance Management 68

Jet Global

FEBRUARY 23, 2024

Load : Once data transformation is complete, the transformed data is loaded into the target system, such as a data warehouse, database, or another application. ETL tools ensure that the data is loaded efficiently and accurately into the destination. Data warehouses can be complex, time-consuming, and expensive.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52