Ontotext

MAY 2, 2024

They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Ontotext

NOVEMBER 16, 2023

Data mesh is still in its infancy, and data personas and organizations are craving clarity and specificity. It is critical to be aware of the “why” and “what” and fully understand the role that knowledge graphs play when considering adopting a data mesh strategy. The debate on what constitutes a data mesh rages on.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 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. Here are a few common data management challenges: Regulatory compliance on data use. Data quality.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

Timo Elliott

DECEMBER 14, 2022

Most innovation platforms make you rip the data out of your existing applications and move it to some another environment—a data warehouse, or data lake, or data lake house or data cloud—before you can do any innovation. The analysts call this a data mesh or data fabric strategy.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

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. So questions linger about whether transformed data can be trusted. Data Quality Obstacles.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

JANUARY 26, 2023

Data is a key asset for businesses in the modern world. Used correctly, it can improve internal operations, power marketing strategies, and much more. That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. This is why data also needs to be compliant.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Ontotext

MARCH 8, 2023

Solution Outcomes: A semantic recommendation service that is beating accuracy benchmarks and replacing manual processes aggregating content – that is supporting higher-quality, more advanced, and targeted recommendations with clear reasons. million users. A risk issue in one financial institution could result in a domino effect for many.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

AWS Big Data

MAY 7, 2024

Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog. The producer also needs to manage and publish the data asset so it’s discoverable throughout the organization.

Metadata 72

Metadata Data Lake Data Processing Data-driven 72

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Octopai

DECEMBER 12, 2021

What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Without metadata, data is just a heap of numbers and letters collecting dust. Where does metadata come from?

Metadata 93

Metadata Management Data Quality Data Governance 93

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. Architectures became fabrics.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

AWS Big Data

FEBRUARY 1, 2023

This introduces the need for both polling and pushing the data to access and analyze in near-real time. Implementation strategy Based on these requirements, we changed strategies and started analyzing each issue to identify the solution. We also used AWS Lambda for data processing.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

CIO Business Intelligence

MARCH 9, 2022

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. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 106

Data Lake Unstructured Data Data Warehouse Data Quality 106

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. It’s obvious that you’ll want to use big data, but it’s not so obvious how you’re going to work with it. Preserve information: Keep your raw data raw.

Metadata 100

Metadata Visualization Unstructured Data Data mining 100

Alation

OCTOBER 21, 2021

That dirty data then corrupts analyses and forces mistakes. A frequent and periodic data cleansing strategy is. Lack of metadata. A lack of organization is another sign of a data swamp, typically driven by bad or incomplete metadata. Ungoverned data.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 129

IT Business Intelligence Sales Key Performance Indicator 129

AWS Big Data

MARCH 1, 2024

As they continue to implement their Digital First strategy for speed, scale and the elimination of complexity, they are always seeking ways to innovate, modernize and also streamline data access control in the Cloud. BMO has accumulated sensitive financial data and needed to build an analytic environment that was secure and performant.

Data Lake 95

Data Lake Data Warehouse Management Risk 95

AWS Big Data

FEBRUARY 13, 2023

We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

Snapshot 64

Snapshot Data Warehouse Testing Analytics 64

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.

Cost-Benefit 82

Cost-Benefit Metadata Optimization Management 82

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52

BI-Survey

FEBRUARY 23, 2023

“Data culture eats data strategy for breakfast” has become a popular saying among data and analytics managers and executives. Even the best data strategy cannot fulfill its potential if the data culture in the company does not match it. These include tools for metadata management (e.g.,

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

Alation

AUGUST 11, 2021

The three of us talked migration strategy and the best way to move to the Snowflake Data Cloud. As Vice President of Data Governance at TMIC, Anthony has robust experience leading cloud migration as part of a larger data strategy. This underscores the importance of having a plan that fits your data strategy.

Data Governance 52

Data Governance Insurance Metadata Strategy 52

DataKitchen

JUNE 24, 2021

Previously we would have a very laborious data warehouse or data mart initiative and it may take a very long time and have a large price tag. Before we jump into a methodology or even a data strategy-based approach, what are we trying to accomplish? Bergh added, “ DataOps is part of the data fabric.

ROI 211

ROI Metrics Measurement Cost-Benefit 211

Smart Data Collective

OCTOBER 13, 2021

Data Virtualization can include web process automation tools and semantic tools that help easily and reliably extract information from the web, and combine it with corporate information, to produce immediate results. How does Data Virtualization manage data quality requirements? In improving operational processes.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

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 64

Data Architecture Data Lake Machine Learning Data Governance 64

erwin

JULY 17, 2019

Having a clearly defined digital transformation strategy is an essential best practice for successful digital transformation. But what makes a viable digital transformation strategy? Constructing A Digital Transformation Strategy: Data Enablement. With automation, data quality is systemically assured.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Ontotext

FEBRUARY 12, 2024

Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh. Once accomplished, an effective implementation spurs a mindset in which organizations prioritize and value data for decision-making, formulating strategies, and day-to-day operations.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

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 107

Unstructured Data Cost-Benefit Metadata Machine Learning 107

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. Strategy is Learning By Doing. Age maybe against us. Some don’t understand the difference.

Analytics 68

Analytics Metadata Data Governance Management 68

Andrew White

JANUARY 11, 2021

Do you recommend a consulting approach strategy rather than a CDO strategy? How do you think Technology Business Management plays into this strategy? Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52