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

CIO Business Intelligence

JULY 18, 2022

We have to make sure we have the processes, the tools, and the teams aligned to make sure they’re optimized, to make sure they’re secure, and to make sure that we have the right digital footprint to coordinate all those efforts.”. We didn’t have basic things like a data warehouse. Analytics, CIO 100, Data Management

Data Warehouse 134

Data Warehouse Dashboards Reporting Manufacturing 134

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 116

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 116

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 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

Cloudera

MAY 16, 2019

The conference provides a useful opportunity to reflect on the rapid evolution we’ve seen in the Data Integration and Management space, much of it driven by the innovations that Cloudera and the open source community have been delivering. The traditional Data Warehouse ETL process has splintered into many smaller components.

Analytics 40

Analytics Data Warehouse Data-driven Data Integration 40

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 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Smart Data Collective

JULY 20, 2021

Whether it is closing more sales deals, getting leads, offering vital customer services, marketing automation, analytics or application development, Salesforce CRM provides a bucket of comprehensive solutions. This tool is designed to connect various data sources, enterprise applications and perform analytics and ETL processes.

Sales 141

Sales Big Data Marketing Software 141

AWS Big Data

MARCH 29, 2024

Analyzing historical patterns allows you to optimize performance, identify issues proactively, and improve planning. You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. The sample dashboard showed metrics over time, top errors, and comparative job analytics.

Metrics 101

Metrics Visualization Dashboards Interactive 101

BizAcuity

MAY 16, 2022

When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. We get critical business insights based on how well we leverage our business data. The more effectively a company uses data, the better it performs. Data Integration.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. The upgrade also offers support for Bloom filters and skew optimization.

Testing 74

Testing Data Lake Cost-Benefit Data Integration 74

CIO Business Intelligence

MARCH 16, 2022

CIO Middle East: Data Analytics is key in healthcare. When we look into the analytics scenario of healthcare, the accurate word to describe it is ‘clinical business intelligence’. The same goes for the adoption of data warehouse and business intelligence. How you see the role of business intelligence in healthcare?

Technology 106

Technology Digital Transformation Business Intelligence Data Warehouse 106

Jet Global

OCTOBER 7, 2020

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

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. Deciding on KPIs to gauge a data architecture’s effectiveness.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

NOVEMBER 20, 2023

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. The end benefit for you is more effective and optimized AWS Glue for Apache Spark workloads.

Metrics 92

Metrics Data Lake Cost-Benefit Dashboards 92

AWS Big Data

OCTOBER 20, 2023

One of the data sources you can now quickly integrate with is Azure Blob Storage, a managed service for storing both unstructured data and structured data, and Azure Data Lake Storage, a data lake for analytics workloads. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Data Lake 80

Data Lake Big Data Consulting Data Warehouse 80

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. Cloudera recognizes that machine learning is built on data management; integrated data, workflows, metadata, security, and governance.

Management 42

Management Metadata Analytics Machine Learning 42

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. Brian Ross is a Senior Software Development Manager at AWS.

Data Quality 92

Data Quality Statistics Data Lake Visualization 92

Cloudera

JUNE 2, 2022

What is less frequently mentioned is that during this same time we have also seen a rapid increase of cloud services where data needs to be delivered (data lakes, lakehouses, cloud warehouses, cloud streaming systems, cloud business processes, etc.). bridging protocols, data formats, routing, filtering, error handling, retries).

Enterprise 98

Enterprise Data Lake Data Collection Data-driven 98

AWS Big Data

FEBRUARY 8, 2023

Vyaire developed a custom data integration platform, iDataHub, powered by AWS services such as AWS Glue , AWS Lambda , and Amazon API Gateway. In this post, we share how we extracted data from SAP ERP using AWS Glue and the SAP SDK. Prahalathan M is the Data Integration Architect at Vyaire Medical Inc.

Testing 70

Testing Data Integration Data Lake Enterprise 70

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

CIO Business Intelligence

JULY 13, 2022

What is less frequently mentioned is that during this same time we have also seen a rapid increase of cloud services where data needs to be delivered (data lakes, lakehouses, cloud warehouses, cloud streaming systems, cloud business processes, etc.). bridging protocols, data formats, routing, filtering, error handling, retries).

Enterprise 65

Enterprise Data Lake Data Collection Data-driven 65

Andrew White

OCTOBER 22, 2021

Analytics Tactics (known outcome/known data/BI/analytics v unknown outcome/unknown data/data science/ML) 11. Data Hub Strategy 10. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Integration tactics 4.

IT 52

IT Data Lake Strategy Data Science 52

AWS Big Data

JULY 31, 2023

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand. Wait for all the jobs to complete.

Sales 52

Sales Data Warehouse Visualization Testing 52

IBM Big Data Hub

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

FineReport

MAY 31, 2023

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs). Data Security : Financial data is highly sensitive and requires robust security measures.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 92

Analytics Visualization Data Integration Cost-Benefit 92

AWS Big Data

FEBRUARY 1, 2023

This introduces the need for both polling and pushing the data to access and analyze in near-real time. From an operational standpoint, we designed a new shared responsibility model for data ingestion using AWS Glue instead of internal services (REST APIs) designed on Amazon EC2 to extract the data.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

JULY 25, 2023

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. Prerequisites To complete the integration, you need a Redshift Serverless data warehouse.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

AWS Big Data

JULY 13, 2023

He has been leading the building of data warehouses and analytic solutions for the past 20 years. Jason Yung is a Principal Analytics Specialist with Amazon Web Services. The Altron team created an AWS Glue crawler and configured it to run against Azure SQL to discover its tables.

Optimization 87

Optimization B2B Data Quality Sales 87

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 89

Data Lake Data Warehouse Metadata Data Architecture 89

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

NOVEMBER 29, 2023

You also need services to store data for analysis and machine learning (ML) like Amazon Simple Storage Service (Amazon S3). Customers have created hundreds of thousands of data lakes on Amazon S3. It does all of this while factoring in your price/performance targets so you can optimize between cost and performance.

Data Warehouse 109

Data Warehouse Data Lake Data Integration Dashboards 109

CIO Business Intelligence

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. For data warehouses, it can be a wide column analytical table. Data and cloud strategy must align.

Data Architecture 106

Data Architecture Data Integration IoT Strategy 106

CIO Business Intelligence

MARCH 22, 2022

How do you introduce AI into your data and analytics infrastructure? To companies entrenched in decades-old business and IT processes, data fiefdoms, and legacy systems, the task may seem insurmountable. Another option is a data warehouse, which stores processed and refined data. Outcomes you can expect.

Analytics 105

Analytics Key Performance Indicator Data Warehouse Data-driven 105

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 77

Data Lake Data Warehouse Data-driven Optimization 77

Data Virtualization

MAY 5, 2020

Bring any data to any data consumer, simply and easily: that’s the goal of data virtualization. Yet contrary to what may first come to mind, data consumers are more than simply BI, analytics, or data science applications. Just about every.

Data Science 52

Data Science Analytics OLAP Optimization 52