CIO Business Intelligence

AUGUST 9, 2024

The original proof of concept was to have one data repository ingesting data from 11 sources, including flat files and data stored via APIs on premises and in the cloud, Pruitt says. He is a very visual person, so our proof of concept collects different data sets and ingests them into our Azure data house.

Data Transformation 126

Data Transformation Machine Learning Data Lake Dashboards 126

CIO Business Intelligence

OCTOBER 18, 2022

“In the old stadium, we just didn’t have the ability to get the data that we needed,” says Machelle Noel, manager of analytic systems at the Texas Rangers Baseball Club. Analytics, Data Management Some of our systems were old. We just didn’t have the ability that we now have in this new, state-of-the-art facility.”.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

Data Lake 92

Data Lake Data Transformation Data-driven Cost-Benefit 92

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Enhance agility by localizing changes within business domains and clear data contracts. Eliminate centralized bottlenecks and complex data pipelines.

IoT 101

IoT Machine Learning Metadata Data-driven 101

CIO Business Intelligence

JUNE 29, 2022

Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

APRIL 27, 2023

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

Data Lake 81

Data Lake Snapshot Optimization Data Transformation 81

AWS Big Data

DECEMBER 20, 2024

The DataFrame code generation now extends beyond AWS Glue DynamicFrame to support a broader range of data processing scenarios. Your generated jobs can use a variety of data transformations, including filters, projections, unions, joins, and aggregations, giving you the flexibility to handle complex data processing requirements.

Data Integration 94

Data Integration Visualization Data Processing Data Lake 94

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

AWS Big Data

AUGUST 9, 2024

With the ever-increasing volume of data available, Dafiti faces the challenge of effectively managing and extracting valuable insights from this vast pool of information to gain a competitive edge and make data-driven decisions that align with company business objectives. We started with 115 dc2.large

Data Lake 107

Data Lake Analytics Data Warehouse Data-driven 107

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. About the author Naidu Rongal i is a Big Data and ML engineer at Amazon.

Metadata 89

Metadata Data Lake Modeling Data Warehouse 89

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 104

Data Warehouse Analytics Data Lake Data Science 104

AWS Big Data

OCTOBER 23, 2024

Let’s expand the use case to run your data pipeline and perform extract, transform, and load (ETL) jobs when a new file lands in an Amazon Simple Storage Service (Amazon S3) bucket in your data lake. The modified architecture to support the data-aware scheduling is presented below.

Interactive 101

Interactive Testing Data-driven Data Lake 101

CIO Business Intelligence

APRIL 8, 2025

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration.

Analytics 108

Analytics IT Data Lake Visualization 108

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 117

Data Lake Management Metrics Data Warehouse 117

AWS Big Data

JANUARY 27, 2023

The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos. Apache Flink is a widely used data processing engine for scalable streaming ETL, analytics, and event-driven applications. Transformed data can be stored in Amazon S3.

Data Lake 67

Data Lake Metadata Business Analysis Data-driven 67

AWS Big Data

AUGUST 19, 2024

By using AWS Glue to integrate data from Snowflake, Amazon S3, and SaaS applications, organizations can unlock new opportunities in generative artificial intelligence (AI) , machine learning (ML) , business intelligence (BI) , and self-service analytics or feed data to underlying applications.

Analytics 108

Analytics Data-driven Data Integration Data Lake 108

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 101

Metadata Data Lake Visualization Data Quality 101

AWS Big Data

APRIL 30, 2024

Amazon Q Developer can now generate complex data integration jobs with multiple sources, destinations, and data transformations. Generated jobs can use a variety of data transformations, including filter, project, union, join, and custom user-supplied SQL. In his spare time, he enjoys cycling with his road bike.

Data Integration 117

Data Integration Data Lake Data Warehouse Software 117

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 111

Analytics Visualization Data Integration Cost-Benefit 111

AWS Big Data

APRIL 26, 2023

To enable this use case, we used the BMW Group’s cloud-native data platform called the Cloud Data Hub. In 2019, the BMW Group decided to re-architect and move its on-premises data lake to the AWS Cloud to enable data-driven innovation while scaling with the dynamic needs of the organization.

Forecasting 130

Forecasting Manufacturing Data Lake Big Data 130

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

AWS Big Data

JUNE 29, 2023

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

Data Analytics 85

Data Analytics Analytics IoT Data Lake 85

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. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

FEBRUARY 16, 2023

“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. For that, he relied on a defensive and offensive metaphor for his data strategy. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

DECEMBER 4, 2024

These nodes can implement analytical platforms like data lake houses, data warehouses, or data marts, all united by producing data products. Domain-owned data assets – The domain-oriented data ownership approach distributes responsibility for data across the business units within the Institutional Division.

Metadata 94

Metadata Data Governance Data Quality Data-driven 94

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 104

Data Lake Data Warehouse Data-driven B2B 104

AWS Big Data

MAY 9, 2023

Hundreds of thousands of customers use AWS Glue , a serverless data integration service, to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue for Apache Spark jobs work with your code and configuration of the number of data processing units (DPU).

Data Lake 101

Data Lake Cost-Benefit Data Integration Data Transformation 101

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 88

Data Lake Data Warehouse Data Architecture Metadata 88

AWS Big Data

DECEMBER 5, 2023

This cut down significantly on analytical turnaround times. The CARTO Analytics Toolbox for Redshift is composed of a set of user-defined functions and procedures organized in a set of modules based on the functionality they offer. Kiran Kumar Tati is an Analytics Specialist Solutions Architect based out of Omaha, NE.

Measurement 94

Measurement Dashboards Data Warehouse Analytics 94

AWS Big Data

SEPTEMBER 5, 2024

Amazon Redshift , a warehousing service, offers a variety of options for ingesting data from diverse sources into its high-performance, scalable environment. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 107

IoT Data Warehouse Cost-Benefit Reporting 107

CIO Business Intelligence

OCTOBER 11, 2022

The goal, she explained, is to knock down data silos between those groups, using multiple data lakes supported by strong security and governance, to drive positive impact across the supply chain, manufacturing, and the clinical trials of new drugs. . Four ways to improve data-driven business transformation .

Machine Learning 145

Machine Learning Data Science Data-driven Testing 145

AWS Big Data

DECEMBER 16, 2024

With the ability to browse metadata, you can understand the structure and schema of the data source, identify relevant tables and fields, and discover useful data assets you may not be aware of. About the Authors Chiho Sugimoto is a Cloud Support Engineer on the AWS Big Data Support team.

Visualization 72

Visualization Data Processing Testing Publishing 72

Cloudera

OCTOBER 11, 2021

Modak’s Nabu is a born in the cloud, cloud-neutral integrated data engineering platform designed to accelerate the journey of enterprises to the cloud. Modak empowers organizations to maximize their ROI from existing analytics infrastructure through interoperability. Modak Nabu TM and CDE’s Spark-on-Kubernetes.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The firm also worked on creating a solid pipeline from the data warehouse to the data lake.

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

IBM Big Data Hub

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

Data Warehouse 86

Data Warehouse Data Lake Optimization Data-driven 86