DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It also addresses the need for managing data objects that are frequently refreshed.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

AWS Big Data

FEBRUARY 29, 2024

Working with large language models (LLMs) for enterprise use cases requires the implementation of quality and privacy considerations to drive responsible AI. However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

CIO Business Intelligence

JANUARY 24, 2024

Building a successful data strategy at scale goes beyond collecting and analyzing data,” says Ryan Swann, chief data analytics officer at financial services firm Vanguard. Creating data silos Denying business users access to information because of data silos has been a problem for years.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

DataKitchen

JANUARY 19, 2022

The Matillion data integration and transformation platform enables enterprises to perform advanced analytics and business intelligence using cross-cloud platform-as-a-service offerings such as Snowflake. DataOps recommends that tests monitor data continuously in addition to checks performed when pipelines are run on demand.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

AWS Big Data

DECEMBER 21, 2023

Movement of data across data lakes, data warehouses, and purpose-built stores is achieved by extract, transform, and load (ETL) processes using data integration services such as AWS Glue. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 92

Analytics IT Data Lake Visualization 92

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 84

Metadata Data Lake Visualization Data Transformation 84

Data Virtualization

MARCH 15, 2024

Join us as we embark on a journey to explore this intriguing domain, unravelling its core principles, diverse applications, associated benefits, The post Hyper-Personalization in Banking: Principles, Applications, Benefits, and Best Practices appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and (..)

Interactive 64

Interactive Data Integration Management Predictive Analytics 64

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

erwin

JANUARY 30, 2020

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

Ontotext

JANUARY 26, 2023

This might include a range of tasks such as searching weather conditions on an app, looking at the temperature at home, reviewing electricity usage on a dedicated web platform, all the way to managing and utilizing data in a professional system at work. And this is what semantic data management is about.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

Jedox

FEBRUARY 13, 2020

The power of artificial intelligence (AI) lies within its ability to make sense of large amounts of data. For the increasing support of planning, budgeting and controlling processes through advanced analytics and AI solutions, powerful data management and data integration are an indispensable prerequisite.

Forecasting 58

Forecasting Predictive Analytics Sales Data Integration 58

Alation

JUNE 23, 2023

That’s going to be the view at the highly anticipated gathering of the global data, analytics, and AI community — Databricks Data + AI Summit — when it makes its grand return to San Francisco from June 26–29. Just having data doesn’t mean your organization is equipped to make critical data-driven decisions.

Data-driven 52

Data-driven Data Processing Data Quality Enterprise 52

CIO Business Intelligence

APRIL 28, 2022

Its success is one of many instances illustrating how the financial services industry is quickly recognizing the benefits of data analytics and what it can offer, especially in terms of risk management automation, customized experiences, and personalization. . million in insurance fraud in just 7 months. .

Analytics 98

Analytics Insurance Big Data Uncertainty 98

CIO Business Intelligence

SEPTEMBER 2, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

JUNE 13, 2022

As with all financial services technologies, protecting customer data is extremely important. In some parts of the world, companies are required to host conversational AI applications and store the related data on self-managed servers rather than subscribing to a cloud-based service. Intel® Technologies Move Analytics Forward.

Data Processing 105

Data Processing Deep Learning Insurance Cost-Benefit 105

Ontotext

JUNE 10, 2021

For instance, the analysis of M&A transactions in order to derive investment insights requires the raw transaction data, in addition to the information on relationships of the companies involved in these transactions, e.g. subsidiaries, joint ventures, investors or competitors. Schemas are powerful. It provides meaning.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

BI-Survey

AUGUST 1, 2019

Data is a central resource in the 21st century. Only those who manage to extract value from their data will remain competitive. For this reason, many organizations are looking at innovative ways of using their data to create value. Providing results for process improvement is the main way to monetize data.

Cost-Benefit 53

Cost-Benefit Reporting Data Quality Data-driven 53

AWS Big Data

JANUARY 30, 2023

This organization is planning to build a data analytical platform, and the insurance policy data is one of the inputs to this platform. Solution overview The data can originate from any source, but typically customers want to bring operational data to data lakes to perform data analytics.

Insurance 75

Insurance Data Lake Data-driven Management 75

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 90

Management Metadata Data Architecture Data Lake 90

DataKitchen

APRIL 13, 2021

Testing and Data Observability. Sandbox Creation and Management. Process Analytics. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Meta-Orchestration.

Testing 307

Testing Machine Learning Consulting Data Quality 307

DataKitchen

MAY 10, 2021

That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. We see data observability as a component of DataOps. In our definition of data observability, we put the focus on the important goal of eliminating data errors.

Testing 214

Testing Manufacturing Data Quality Statistics 214

AWS Big Data

JULY 13, 2023

This is a guest post co-authored by Jacques Steyn, Senior Manager Professional Services at Altron Group. Altron is a pioneer of providing data-driven solutions for their customers by combining technical expertise with in-depth customer understanding to provide highly differentiated technology solutions.

Optimization 87

Optimization B2B Data Quality Sales 87

Smarten

APRIL 19, 2024

The value of an AI-focused analytics solution can only be fully realized when a business has ensured data quality and integration of data sources, so it will be important for businesses to choose an analytics solution and service provider that can help them achieve these goals.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

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. times better performance than the self-managed version.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

erwin

FEBRUARY 4, 2021

However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Overcoming Data Governance Bottlenecks. Put data quality first : Users must have confidence in the data they use for analytics.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. Data integration. Start a trial.

Data-driven 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

AWS Big Data

JULY 12, 2023

Introduction to Amazon Redshift Amazon Redshift is a fast, fully-managed, self-learning, self-tuning, petabyte-scale, ANSI-SQL compatible, and secure cloud data warehouse. Thousands of customers use Amazon Redshift to analyze exabytes of data and run complex analytical queries.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

AWS Big Data

JUNE 12, 2023

Organizations across the world are increasingly relying on streaming data, and there is a growing need for real-time data analytics, considering the growing velocity and volume of data being collected. Therefore, it’s crucial to keep the schema definition in the Schema Registry and the Data Catalog table in sync.

Management 75

Management Metadata Testing Internet of Things 75

CIO Business Intelligence

MARCH 22, 2022

Then virtualize your data to allow business users to conduct aggregated searches and analyses using the business intelligence or data analytics tools of their choice. . Set up unified data governance rules and processes. With data integration comes a requirement for centralized, unified data governance and security.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

AWS Big Data

JULY 20, 2023

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

Data Lake 83

Data Lake Analytics Snapshot Optimization 83

Andrew White

JANUARY 9, 2022

Here is a recent note on synthetic data: Maverick* Research: Forget About Your Real Data — Synthetic Data Is the Future of AI. What are your thoughts on a data mesh vs. data fabric in large heterogeneous environments? – This is a question for our data management team. Try Mark Beyer.

Analytics 64

Analytics Measurement Modeling Data-driven 64

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

DataRobot Blog

APRIL 1, 2018

Today’s data management and analytics products have infused artificial intelligence (AI) and machine learning (ML) algorithms into their core capabilities. These modern tools will auto-profile the data, detect joins and overlaps, and offer recommendations.

Analytics 40

Analytics IoT Internet of Things B2B 40

IBM Big Data Hub

OCTOBER 12, 2023

The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly. But the implementation of AI is only one piece of the puzzle.

Cost-Benefit 85

Cost-Benefit Metadata Data Governance Modeling 85

Ontotext

FEBRUARY 26, 2024

Bad Data Tax and the Data Bill of Rights So far, our discussion has been pretty theoretical, so we need a compelling business justification for moving in this direction. In the race to become data-driven, most efforts have resulted in a tangled web of data integrations and reconciliations across a sea of data silos.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

datapine

FEBRUARY 22, 2022

Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on. Improved risk management: Another great benefit from implementing a strategy for BI is risk management.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218