CIO Business Intelligence

AUGUST 14, 2024

Organizations with experience building enterprise data lakes connecting to many different data sources have AI advantages. They’re more able to connect to a diverse set of data sources, build more complex context around queries going through the model, and do retrieval augmented generation,” he adds.

Enterprise 135

Enterprise Cost-Benefit Experimentation Modeling 135

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. This popular open-source tool for data warehouse transformations won out over other ETL tools for several reasons. The tool also offered desirable out-of-the-box features like data lineage, documentation, and unit testing.

Data Warehouse 116

Data Warehouse Testing Data Quality Reporting 116

CIO Business Intelligence

OCTOBER 2, 2024

And the other is retrieval augmented generation (RAG) models, where pieces of data from a larger source are vectorized to allow users to “talk” to the data. For example, they can take a thousand-page document, have it ingested by the model, and then ask the model questions about it.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Metadata Data Quality Data Governance 52

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 78

Analytics Data Warehouse Data Lake Metadata 78

CIO Business Intelligence

JULY 31, 2024

A significant Copilot use case has been finding documents. We also have a blended architecture of deep process capabilities in our SAP system and decision-making capabilities in our Microsoft tools, and a great base of information in our integrated data hub, or data lake, which is all Microsoft-based.

Manufacturing 119

Manufacturing Cost-Benefit Digital Transformation Forecasting 119

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.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

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 82

Data Quality Data-driven Data Lake Metrics 82

erwin

JANUARY 11, 2019

A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management. The problem usually starts by relying on manual integration methods for data preparation and mapping.

Data Governance 40

Data Governance Risk Metadata Management 40

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

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 94

Enterprise Data Warehouse Snapshot Cost-Benefit 94

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. 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.

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 111

Data Lake Data Warehouse Risk Management 111

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI).

Data Warehouse 97

Data Warehouse KPI Optimization Cost-Benefit 97

datapine

APRIL 15, 2020

Working software over comprehensive documentation. The agile BI implementation methodology starts with light documentation: you don’t have to heavily map this out. But before production, you need to develop documentation, test driven design (TDD), and implement these important steps: Actively involve key stakeholders once again.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Cloudera

AUGUST 30, 2022

It outlines a scenario in which “recently married people might want to change their names on their driver’s licenses or other documentation. That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. Data quality issues deter trust and hinder accurate analytics.

Data Architecture 83

Data Architecture Data Lake Data Warehouse Metadata 83

Alation

JULY 19, 2022

For example, a new data scientist who is curious about which customers are most likely to be repeat buyers, might search for customer data only to discover an article documenting a previous project that answered their exact question. Modern data catalogs also facilitate data quality checks.

Metadata 59

Metadata Data Quality Statistics Data Science 59

CIO Business Intelligence

JANUARY 30, 2024

“Always the gatekeepers of much of the data necessary for ESG reporting, CIOs are finding that companies are even more dependent on them,” says Nancy Mentesana, ESG executive director at Labrador US, a global communications firm focused on corporate disclosure documents.

Reporting 112

Reporting Data Quality Strategy Data-driven 112

Cloudera

AUGUST 4, 2021

Factors such as siloed platforms and the absence of centralized data stewardship all regularly contribute to a lack of data visibility. . Organizations are facing a data tsunami with more data being generated than ever, making it even more difficult to discover, catalog, and keep track of all this information.

Data Governance 91

Data Governance Metadata Data-driven Enterprise 91

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

IBM Big Data Hub

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

Alation

MARCH 21, 2023

Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

NOVEMBER 15, 2023

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. DataBrew is an excellent tool for data quality and preprocessing.

Metadata 95

Metadata Sales Data Lake Big Data 95

AWS Big Data

JULY 25, 2024

With AWS Glue, you can discover and connect to hundreds of different data sources and manage your data in a centralized data catalog. You can visually create, run, and monitor ETL pipelines to load data into your data lakes. He is responsible for building software artifacts to help customers.

Visualization 98

Visualization Management Data Integration Testing 98

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Alation

SEPTEMBER 23, 2021

Behavioral intelligence, embedded in the catalog, learns from user behavior to enforce best practices through features like data quality flags, which help folks stay compliant as they use data. Active Governance – Active data governance creates usage-based assignments, which prioritize and delegate curation duties.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52

Domino Data Lab

JUNE 15, 2021

At a certain point, as the demand keeps growing, the data volumes rapidly increase. Data is no longer stored in CSV files, but in a dedicated, purpose built data lake / data warehouse. Existing preprocessing, data ingestion, and data quality processes can be converted from Java/Spark into Java UDFs.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

datapine

AUGUST 29, 2022

The new edition also explores artificial intelligence in more detail, covering topics such as Data Lakes and Data Sharing practices. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Alation

AUGUST 4, 2022

And where data was available, the ability to access and interpret it proved problematic. Big data can grow too big fast. Left unchecked, data lakes became data swamps. Some data lake implementations required expensive ‘cleansing pumps’ to make them navigable again.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

Ontotext

AUGUST 21, 2024

The issue is many organizations have massive amounts of data that they collect and store in their relational databases, document stores, data lakes, and data warehouses. But until they connect the dots across their data, they will never be able to truly leverage their information assets.

Knowledge Discovery 52

Knowledge Discovery Cost-Benefit Data-driven Metadata 52

erwin

DECEMBER 13, 2018

As organizations become data-driven and awash in an overwhelming amount of data from multiple data sources (AI, IOT, ML, etc.), organizations will need to get a better handle on data quality and focus on data management processes and practices.

Data Governance 91

Data Governance IoT Internet of Things Data-driven 91

Alation

FEBRUARY 17, 2023

How do you get executives to understand the value of data governance? First, document your successes of good data, and how it happened. Share stories of data in good times and in bad (pictures help!). Some data seems more analytical, while other is operational (external facing). Seeing is believing!

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

IBM Big Data Hub

JULY 27, 2023

Precisely conducted a study that found that within enterprises, data scientists spend 80% of their time cleaning, integrating and preparing data , dealing with many formats, including documents, images, and videos. Overall placing emphasis on establishing a trusted and integrated data platform for AI.

Management 54

Management Enterprise Modeling Data Quality 54

erwin

JULY 17, 2019

Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured. The data pipeline is seamlessly governed and operationalized to the benefit of all stakeholders. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

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

BI-Survey

DECEMBER 22, 2020

Providing an easily accessible description of individual data sources and their dependencies and processing flows is an important step. Data catalog platforms are ideal for this purpose. The usability of data documentation for business users stands and falls with an overarching business glossary.

Data-driven 52

Data-driven Data Strategy Strategy Enterprise 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52