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

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

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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

Data Virtualization

MARCH 7, 2024

One thing is clear; if data-centric organizations want to succeed in. The post Data Management Predictions for 2024: Five Trends appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Management 59

Management Data Integration Strategy Data Lake 59

Data Virtualization

JANUARY 25, 2024

One thing is clear; if data-centric organizations want to succeed in 2024, The post Data Management Predictions for 2024: Five Trends appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Management 59

Management Data Integration Strategy Data Lake 59

Data Virtualization

MARCH 23, 2023

The post 5 Trends in Financial Services That Will Change How You Think about Your Data appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Interactive 52

Interactive Data Integration Technology Management 52

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 88

Data Analytics Analytics Data Warehouse Data Lake 88

Data Virtualization

MARCH 23, 2023

The post <strong>5 Trends in Financial Services That Will Change How You Think about Your Data</strong> appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Interactive 52

Interactive Data Integration Technology Management 52

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

AWS Big Data

DECEMBER 15, 2023

Many companies identify and label PII through manual, time-consuming, and error-prone reviews of their databases, data warehouses and data lakes, thereby rendering their sensitive data unprotected and vulnerable to regulatory penalties and breach incidents. Load data from Amazon S3 to the Redshift data warehouse.

Data Lake 100

Data Lake Data Warehouse Big Data Structured Data 100

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

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. What role do technology and IT infrastructure play?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

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. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

IBM Big Data Hub

APRIL 27, 2022

The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. Read: The first capability of a data fabric is a semantic knowledge data catalog, but what are the other 5 core capabilities of a data fabric? 11 May 2021. .

Management 88

Management Metadata Data Architecture Data Lake 88

CIO Business Intelligence

MAY 24, 2022

The survey found the mean number of data sources per organisation to be 400, and more than 20 percent of companies surveyed to be drawing from 1,000 or more data sources to feed business intelligence and analytics systems. However, more than 99 percent of respondents said they would migrate data to the cloud over the next two years.

Data-driven 98

Data-driven Data Lake Data Warehouse Cost-Benefit 98

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

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. A set of QuickSight dashboards to be consumed via browser and mobile.

Optimization 87

Optimization B2B Data Quality Sales 87

Data Virtualization

SEPTEMBER 16, 2020

Organizations are leveraging cloud analytics to extract useful insights from big data, which draws from a variety of sources such as mobile phones, Internet of. Organizations all over the world are migrating their IT infrastructures and applications to the cloud.

Big Data 59

Big Data Internet of Things Analytics IT 59

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 66

Modeling Sales Data Warehouse Snapshot 66

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 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 83

Cost-Benefit Metadata Data Governance Modeling 83

Data Virtualization

MAY 19, 2021

The post Credit Agricole Leverages the Denodo Platform to Streamline Data Access appeared first on Data Virtualization blog.

Management 52

Management Data Lake Data Warehouse Data Integration 52

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

BI-Survey

APRIL 27, 2023

Lessons about data modeling, modernization, and automation include the following: Focus on fundamentals Companies place the highest priority on data quality, ease of use, analytics performance, and data governance. The lakehouse, data fabric, and data mesh have 8-12% usage each.

Modeling 52

Modeling Data Warehouse Data Quality Business Driver 52

Data Virtualization

JANUARY 30, 2019

In this article, I will discuss the complexity of data migration when transitioning to a new system, based on the traditional ways of working. I will explain why data virtualization can play a role in taking away this complexity, for. The post How Much Time Could Your Company Save If You Said Goodbye to Data Migration?

Management 40

Management Data Lake Data Warehouse Data Integration 40

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 80

Machine Learning Metrics Management Big Data 80

AWS Big Data

NOVEMBER 13, 2023

11:30 AM – 12:30 PM (PDT) Ceasars Forum ANT318 | Accelerate innovation with end-to-end serverless data architecture. 4:30 PM – 5:30 PM (PDT) Wynn ANT207 | Understand your data with business context. 1:00 PM – 2:00 PM (PDT) Venetian ANT201 | Accelerate innovation with real-time data.

Analytics 110

Analytics Data Lake Data Warehouse Data-driven 110

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 64

Data Architecture Data Lake Machine Learning Data Governance 64

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

erwin

JULY 17, 2019

The solution is data intelligence. It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement. Organizations need a real-time, accurate picture of the metadata landscape to: Discover data – Identify and interrogate metadata from various data management silos.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52