CIO Business Intelligence

OCTOBER 18, 2022

With the new stadium on the horizon, the team needed to update existing IT systems and manual business and IT processes to handle the massive volumes of new data that would soon be at their fingertips. “In The process included co-developing a comprehensive roadmap, project plan, and budget with the business operations team.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

CIO Business Intelligence

JUNE 29, 2022

Analytics is the means for discovering those insights, and doing it well requires the right tools for ingesting and preparing data, enriching and tagging it, building and sharing reports, and managing and protecting your data and insights. Azure Data Factory. Azure Data Lake Analytics. Microsoft.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

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 94

Data Warehouse Data Lake Analytics Data Science 94

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 84

Data Lake Data Architecture Metadata Data Warehouse 84

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 82

Cost-Benefit Metadata Optimization Management 82

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

IBM Big Data Hub

JULY 17, 2023

Additional capabilities of our ML and data science toolkit include: MLOps pipelines: Offers a collaborative studio for data scientists to build, train and deploy machine learning models with advanced features like automated machine learning and model monitoring. ” Vitaly Tsivin, EVP Business Intelligence at AMC Networks.

Machine Learning 66

Machine Learning Data Warehouse Modeling Cost-Benefit 66

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 77

Data Quality Testing Data Warehouse Unstructured Data 77

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 106

Data Lake Management Metrics Data Warehouse 106

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

AUGUST 1, 2023

In the world of software engineering and development, organizations use project management tools like Atlassian Jira Cloud. Managing projects with Jira leads to rich datasets, which can provide historical and predictive insights about project and development efforts. An AWS account and a login with access to the AWS Management Console.

Data Lake 86

Data Lake Data Transformation Cost-Benefit Data-driven 86

AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. They used Amazon Aurora MySQL zero-ETL integration with Amazon Redshift to achieve this.

Dashboards 75

Dashboards Data-driven Data Integration Data Lake 75

CIO Business Intelligence

OCTOBER 11, 2022

This initiative alone has generated an explosion in the quantity and complexity of data the company collects, stores, and analyzes for insights. . “We What began as an initiative focused on R&D now has extended to the company’s three other major business units: Commercial, Operations, and Clinical, according to Kaur.

Machine Learning 145

Machine Learning Data-driven Testing Data Science 145

CIO Business Intelligence

AUGUST 3, 2023

It also helps him democratize credit union data so it can be used to improve customer service, automate the maintenance of such data by making various types of data easier to find, and provide chains of custody and audit controls to help meet regulatory needs.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 92

Data Lake Data Warehouse Data-driven B2B 92

AWS Big Data

APRIL 5, 2023

The company decided to use AWS to unify its business intelligence (BI) and reporting strategy for both internal organization-wide use cases and in-product embedded analytics targeted at its customers. The company also used the opportunity to reimagine its data pipeline and architecture.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52