CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

OCTOBER 25, 2023

Text, images, audio, and videos are common examples of unstructured data. Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly.

Unstructured Data 123

Unstructured Data Metadata Management Analytics 123

Ontotext

JANUARY 10, 2024

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. In both cases, semantic metadata is the glue that turns knowledge graphs into hubs of data, metadata, and content.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Ontotext

NOVEMBER 11, 2024

Knowledge graphs, while not as well-known as other data management offerings, are a proven dynamic and scalable solution for addressing enterprise data management requirements across several verticals. With the help of natural language processing (NLP), text documents can also be integrated with knowledge graphs.

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52

CIO Business Intelligence

MARCH 24, 2023

It must be clear to all participants and auditors how and when data-related decisions and controls were introduced into the processes. Data-related decisions, processes, and controls subject to data governance must be auditable. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Alation

MAY 31, 2023

This means that specialized roles such as data architects, which focus on modernizing data architecture to help meet business goals, are increasingly important to support data governance. What is a data architect? Their broad range of responsibilities include: Design and implement data architecture.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

erwin

SEPTEMBER 17, 2020

For example, automatically importing mappings from developers’ Excel sheets, flat files, Access and ETL tools into a comprehensive mappings inventory, complete with auto generated and meaningful documentation of the mappings, is a powerful way to support overall data governance. Data quality is crucial to every organization.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. Metadata management is the key to managing and governing your data and drawing intelligence from it. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Enterprise Modeling Management 93

AWS Big Data

SEPTEMBER 7, 2023

AWS Glue Data Catalog stores information as metadata tables, where each table specifies a single data store. The AWS Glue crawler writes metadata to the Data Catalog by classifying the data to determine the format, schema, and associated properties of the data. Enable access logging on an S3 bucket.

Metadata 106

Metadata Dashboards Metrics Visualization 106

TDAN

AUGUST 18, 2020

Consistent business meaning is important because distinctions between business terms are not typically well defined or documented. Standards exist for naming conventions, abbreviations and other pertinent metadata properties. What are the standards for writing […].

Management 96

Management Metadata Data Architecture IT 96

erwin

JULY 12, 2019

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. Five Steps to GDPR/CCPA Compliance. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

CIO Business Intelligence

MARCH 6, 2024

The company is expanding its partnership with Collibra to integrate Collibra’s AI Governance platform with SAP data assets to facilitate data governance for non-SAP data assets in customer environments. “We We are also seeing customers bringing in other data assets from other apps or data sources.

Unstructured Data 129

Unstructured Data Dashboards Business Intelligence Data Governance 129

AWS Big Data

OCTOBER 1, 2024

However, even the most powerful systems can experience performance degradation if they encounter anti-patterns like grossly inaccurate table statistics, such as the row count metadata. This can have a significant impact on overall query performance.

Data Lake 98

Data Lake Statistics Broadcasting Optimization 98

Cloudera

SEPTEMBER 28, 2020

Review the Upgrade document topic for the supported upgrade paths. Document the number of dev/test/production clusters. Document the operating system versions, database versions, and JDK versions. Review the JDK versions and determine if a JDK version change is needed and if so follow the documentation here to upgrade.

Testing 132

Testing Metadata Risk Data Science 132

Alation

MARCH 31, 2023

Ehtisham Zaidi, Gartner’s VP of data management, and Robert Thanaraj, Gartner’s director of data management, gave an update on the fabric versus mesh debate in light of what they call the “active metadata era” we’re currently in. The foundations of successful data governance The state of data governance was also top of mind.

Data Analytics 52

Data Analytics Analytics Metadata Data Governance 52

Octopai

APRIL 8, 2020

While there are many factors that led to this event, one critical dynamic was the inadequacy of the data architectures supporting banks and their risk management systems. It required banks to maintain data architecture supporting risk aggregation at all times. Download the Whitepaper.

Finance 52

Finance Cost-Benefit Metadata Data Architecture 52

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. Edge computing can be decentralized from on-premises, cellular, data centers, or the cloud.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 118

Data Lake Analytics Dashboards Metrics 118

Octopai

JULY 9, 2020

When conducted manually, however, which has tended to be the normal mode of operation before companies discovered automation – or machine learning data lineage solutions, data lineage can be extremely tedious and time-consuming for BI & Analytics teams. A key piece of legislation that emerged from that crisis was BCBS-239.

Insurance 98

Insurance Risk Management Machine Learning Metadata 98

AWS Big Data

MARCH 25, 2024

A RAG-based generative AI application can only produce generic responses based on its training data and the relevant documents in the knowledge base. Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently.

Data Lake 97

Data Lake Unstructured Data Management Snapshot 97

AWS Big Data

NOVEMBER 7, 2024

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. Amazon Redshift is a fully managed data warehouse service offered by Amazon Web Services (AWS).

Data Warehouse 77

Data Warehouse Reporting Big Data Data Lake 77

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 119

Data Lake Metadata Statistics Optimization 119

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. The complexity is at a much higher level.”

Reporting 115

Reporting Data Quality Strategy Data-driven 115

Sisense

JULY 6, 2020

First off, this involves defining workflows for every business process within the enterprise: the what, how, why, who, when, and where aspects of data. Its main purpose is to establish an enterprise data management strategy. These regulations, ultimately, ensure key business values: data consistency, quality, and trustworthiness.

Enterprise 98

Enterprise Management Data Architecture Data-driven 98

Alation

FEBRUARY 20, 2020

to catalog enterprise data by observing analyst behaviors. Our approach was contrasted with the traditional manual wiki of notes and documentation and labeled as a modern data catalog. We envisioned and learnt from the early production customer implementations that cataloging data wasn’t enough.

Metadata 52

Metadata Enterprise Data Processing Data Architecture 52

AWS Big Data

JANUARY 22, 2024

Cost and resource efficiency – This is an area where Acast observed a reduction in data duplication, and therefore cost reduction (in some accounts, removing the copy of data 100%), by reading data across accounts while enabling scaling. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 93

Data-driven Advertising Metadata Data Architecture 93

AWS Big Data

FEBRUARY 7, 2024

Consult your IdP documentation. Download the IAM Identity Center SAML metadata file to use in a later step. Choose Import from XML file and import the IAM Identity Center SAML metadata file that you downloaded in an earlier step. Luca Menichetti is a Big Data Architect with Amazon Web Services. Create a SAML 2.0

Dashboards 88

Dashboards Data Processing Metadata Consulting 88

AWS Big Data

APRIL 19, 2023

Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights. A modern data architecture is critical in order to become a data-driven organization.

Technology 86

Technology Data-driven Machine Learning Sales 86

TDAN

MAY 31, 2022

One very influential factor that can potentially undermine your data and document strategies is the natural and emotional reactions of people when things change. It is common to take great care in the selection and implementation of new technology.

Testing 52

Testing Interactive Strategy Software 52

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. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

OCTOBER 30, 2024

This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake ( Apache Iceberg ) using AWS Glue. format(add_column)).select("DATA_TYPE").toPandas().iterrows())[0]

Data Lake 95

Data Lake Data Processing Optimization Machine Learning 95

Sisense

SEPTEMBER 3, 2019

Modeling Your Data for Performance. Data architecture. The data landscape has changed significantly over the last two decades. The volume of data being created has increased, and the storage and computational resources needed to store and analyze that data has become cheaper and more widely available.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Andrew White

JANUARY 9, 2022

Is there a good map that shows the connections between data, advanced analytics, digital, innovation, etc. I would have to admit that there are few documents that talk about all the connections across any set of topics. Most of D&A concerns and activities are done within EA in the Info/Data architecture domain/phases.

Analytics 64

Analytics Measurement Data-driven Modeling 64

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 123

Metadata Cost-Benefit Enterprise Interactive 123

DataKitchen

AUGUST 8, 2023

Data Observability leverages five critical technologies to create a data awareness AI engine: data profiling, active metadata analysis, machine learning, data monitoring, and data lineage. Like an apartment blueprint, Data lineage provides a written document that is only marginally useful during a crisis.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130