Ontotext

APRIL 10, 2024

Bad data tax is rampant in most organizations. Currently, every organization is blindly chasing the GenAI race, often forgetting that data quality and semantics is one of the fundamentals to achieving AI success. Sadly, data quality is losing to data quantity, resulting in “ Infobesity ”. “Any

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

APRIL 4, 2024

Griffin is an open source data quality solution for big data, which supports both batch and streaming mode. In today’s data-driven landscape, where organizations deal with petabytes of data, the need for automated data validation frameworks has become increasingly critical.

Data Quality 62

Data Quality Data Lake Data Warehouse Data-driven 62

CIO Business Intelligence

MAY 24, 2022

In order to help maintain data privacy while validating and standardizing data for use, the IDMC platform offers a Data Quality Accelerator for Crisis Response. Cloud Computing, Data Management, Financial Services Industry, Healthcare Industry

Finance 140

Finance Management Metadata Data Quality 140

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

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 81

Data Lake Data Governance Data Architecture Machine Learning 81

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 106

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 106

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake.

Data Warehouse 104

Data Warehouse Testing Data Quality Reporting 104

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 96

Analytics IT Data Lake Visualization 96

Timo Elliott

JANUARY 3, 2022

It’s stored in corporate data warehouses, data lakes, and a myriad of other locations – and while some of it is put to good use, it’s estimated that around 73% of this data remains unexplored. Improving data quality. Unexamined and unused data is often of poor quality. Data augmentation.

IT 143

IT Unstructured Data Data Quality Machine Learning 143

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. Business Context.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

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 78

Data Lake Data Architecture Data-driven Data Warehouse 78

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy.

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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 58

Data-driven Enterprise Data Governance Data Lake 58

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. Ensuring data quality is made easier as a result.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.

Analytics 55

Analytics Data Lake Testing Optimization 55

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

AWS Big Data

JUNE 6, 2023

You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 75

Data Quality Data Lake Data-driven Metrics 75

Jedox

OCTOBER 22, 2020

Gartner defines “dark data” as the data organizations collect, process, and store during regular business activities, but doesn’t use any further. Gartner also estimates 80% of all data is “dark”, while 93% of unstructured data is “dark.”.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

erwin

JANUARY 11, 2019

It’s only when companies take their first stab at manually cataloging and documenting operational systems, processes and the associated data, both at rest and in motion, that they realize how time-consuming the entire data prepping and mapping effort is, and why that work is sure to be compounded by human error and data quality issues.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

NOVEMBER 2, 2022

“At Databricks, we’re focused on enabling customers to adopt the data lakehouse, and that’s an open data architecture that combines the best of the data warehouse and the data lake into one platform,” Ferguson says. “[The And data governance is critical to driving adoption.”.

Data Governance 98

Data Governance Marketing Finance Data Lake 98

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

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Marketing 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

Ontotext

MARCH 8, 2023

As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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 99

Data Lake Data Warehouse Management Risk 99

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. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Data Virtualization

MARCH 7, 2024

Reading Time: 3 minutes As we move deeper into 2024, it is imperative for data management leaders to look in their rear-view mirrors to assess and, if needed, refine their data management strategies. One thing is clear; if data-centric organizations want to succeed in.

Management 59

Management Data Integration Strategy Data Lake 59

Data Virtualization

JANUARY 25, 2024

Reading Time: 3 minutes As we head into 2024, it is imperative for data management leaders to look in their rear-view mirrors to assess and, if needed, refine their data management strategies.

Management 59

Management Data Integration Strategy Data Lake 59

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

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.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Forrester ). Gartner ).

Data Architecture 75

Data Architecture Data Lake Metadata Data Warehouse 75

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.

Optimization 90

Optimization B2B Data Quality Sales 90