AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 112

Data Lake Cost-Benefit Data-driven Data Warehouse 112

Cloudera

MAY 28, 2024

This form of architecture can handle data in all forms—structured, semi-structured, unstructured—blending capabilities from data warehouses and data lakes into data lakehouses.

Data Architecture 88

Data Architecture Data Lake Data Warehouse Cost-Benefit 88

IBM Big Data Hub

APRIL 19, 2023

This work involved creating a single set of definitions and procedures for collecting and reporting financial data. The water company also needed to develop reporting for a data warehouse, financial data integration and operations.

Technology 81

Technology Forecasting Data Warehouse Reporting 81

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

AWS Big Data

APRIL 29, 2024

This system simplifies managing user access, saves time for data security administrators, and minimizes the risk of configuration errors. Addressing big data challenges – Big data comes with unique challenges, like managing large volumes of rapidly evolving data across multiple platforms.

Management 109

Management Big Data Data Warehouse Metadata 109

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. This should also include creating a plan for data storage services. Because it is that important.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement. And do it without the risk of breaking everything.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

FineReport

JULY 16, 2021

When we talk about business intelligence system, it normally includes the following components: data warehouse BI software Users with appropriate analytical. Data analysis and processing can be carried out while ensuring the correctness of data. Data Warehouse. Data Analysis. Features of BI systems.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. SQL Server Integration Services (SSIS): You know it; your father used it.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model?

Data Warehouse 71

Data Warehouse Data Lake Cost-Benefit Metadata 71

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 106

Data Analytics Analytics Data Warehouse Data Lake 106

AWS Big Data

JUNE 27, 2024

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. Document the entire disaster recovery process.

Snapshot 81

Snapshot Data Warehouse Data Processing Strategy 81

AWS Big Data

FEBRUARY 29, 2024

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. The user permissions are evaluated using AWS Lake Formation to filter the relevant data.

Data Governance 110

Data Governance Unstructured Data Metadata Data Lake 110

erwin

FEBRUARY 19, 2021

Is it sensitive or are there any risks associated with it? Metadata also helps your organization to: Discover data. Identify and interrogate metadata from various data management silos. Harvest data. Automate the collection of metadata from various data management silos and consolidate it into a single source.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Jet Global

OCTOBER 7, 2020

Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities. The Data Entity Store is an internal data warehouse that is only available to embedded Power BI reports (not the full version of Power BI).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

BizAcuity

APRIL 1, 2023

Introduction Informatica is a data integration tool based on ETL architecture. It provides data integration software and services for various businesses, industries and government organizations including telecommunication, health care, financial and insurance services. It could be utilized as a tool for cleansing data.

IT 52

IT Data Warehouse Cost-Benefit Data Integration 52

erwin

JANUARY 11, 2019

Consider the problematic issue of manually mapping source system fields (typically source files or database tables) to target system fields (such as different tables in target data warehouses or data marts). So how can businesses produce value from their data when errors are introduced through manual integration processes?

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

JUNE 28, 2023

Furthermore, the time required to build or change pipelines makes the data unfit for near-real-time use cases such as detecting fraudulent transactions, placing online ads, and tracking passenger train schedules.

Analytics 76

Analytics Data Warehouse Data Lake Data-driven 76

IBM Big Data Hub

OCTOBER 30, 2023

Real-time analytics on customer data — made possible by DB2’s high-speed processing on AWS — allows the company to offer personalized insurance packages. AI algorithms sift through large datasets to identify fraud risks and streamline claims processing, improving both efficiency and customer satisfaction.

Insurance 77

Insurance Data Warehouse Data-driven Unstructured Data 77

Jet Global

MAY 1, 2020

In Gartner’s report, an analyst goes to great pains to say that there is “much more risk associated to non-technology issues than there is to deploying the infrastructure, tools, and apps.”. We can almost guarantee you different results from each, and you end up with no data integrity whatsoever. Risk to the business.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

BizAcuity

APRIL 1, 2023

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

AWS Big Data

JULY 25, 2023

The integration of Talend Cloud and Talend Stitch with Amazon Redshift Serverless can help you achieve successful business outcomes without data warehouse infrastructure management. Data scientists, developers, and data analysts can access meaningful insights and build data-driven applications with zero maintenance.

Data Analytics 52

Data Analytics Analytics Data Warehouse Data Processing 52

CIO Business Intelligence

JUNE 7, 2022

Because of this, only a small percentage of your AI team will work on data science efforts, he says. The rest of the team will identify the problem being solved, help explain the data, help organize the data, integrate the output into another production system, or present the data in a presentation-ready manner.”.

Machine Learning 145

Machine Learning Data Science Metrics Consulting 145

Birst BI

OCTOBER 30, 2018

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Add the predictive logic to the data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Enrichment typically involves adding demographic, behavioral, and geolocation data.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

erwin

DECEMBER 12, 2019

Is it sensitive or are there any risks associated with it? The Role of Metadata in Data Governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Where did it come from? Where is it now? How has it changed since it was originally created or captured?

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Cloudera

SEPTEMBER 12, 2022

A data fabric answers perhaps the biggest question of all: what data do we have to work with? Managing and making individual data sources available through traditional enterprise data integration, and when end users request them, simply does not scale — especially in light of a growing number of sources and volume.

Unstructured Data 75

Unstructured Data Data Architecture Data Lake Snapshot 75

BI-Survey

NOVEMBER 23, 2021

However, the operational data stored in data silos was not suitable for this task. Many companies therefore built a data warehouse to consolidate their operational data silos. Data-based insights are being used to automate decisions. Data-based insights are being used to automate decisions.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

BizAcuity

DECEMBER 28, 2022

Informatica is a data integration tool based on ETL architecture. It provides data integration software and services for various businesses, industries and government organizations including telecommunication, health care, financial and insurance services. Data is moved from many databases to the Data warehouse.

IT 40

IT Data Warehouse Cost-Benefit Data Integration 40

Octopai

JUNE 1, 2020

Data mapping is the cornerstone of many important business intelligence processes: Data Integration – Even if systems are compatible, combining two disparate data repositories still requires meticulous data mapping. Correct data mapping facilitates the creation of usable, searchable data warehouses.

Metadata 52

Metadata Data Warehouse Data Integration Enterprise 52

erwin

APRIL 27, 2022

In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Change Data Capture identifies and processes only the data that has changed and stores the changed data in a form so as to be of further use.

Data Governance 52

Data Governance Data Warehouse Metadata Digital Transformation 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

IBM Big Data Hub

AUGUST 4, 2023

Data fabric Data fabric architectures are designed to connect data platforms with the applications where users interact with information for simplified data access in an organization and self-service data consumption. The platform comprises three powerful components: the watsonx.ai

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 83

Data Quality Data-driven Data Lake Metrics 83

Alation

JANUARY 27, 2022

Data analytics is a way to make sense of raw data. Raw data includes market research, sales data, customer transactions, and more. Analytics can identify patterns that depict risks, opportunities, and trends. And historical data can be used to inform predictive analytic models, which forecast the future.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52