CIO Business Intelligence

APRIL 8, 2025

In healthcare, missing treatment data or inconsistent coding undermines clinical AI models and affects patient safety. In retail, poor product master data skews demand forecasts and disrupts fulfillment. In the public sector, fragmented citizen data impairs service delivery, delays benefits and leads to audit failures.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

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 100

Metadata Data Lake Visualization Data Quality 100

DataKitchen

JULY 27, 2023

Azure Functions: You can write small pieces of code (functions) that will do the transformations for you. Azure HDInsight: A fully managed cloud service that makes processing massive amounts of data easy, fast, and cost-effective. Power BI dataflows: Power BI dataflows are a self-service data preparation tool.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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. After moving its expensive, on-premise data lake to the cloud, Comcast created a three-tiered architecture.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

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 129

Forecasting Manufacturing Data Lake Big Data 129

AWS Big Data

MAY 9, 2023

For workloads such as data transforms, joins, and queries, you can use G.1X 2X (2 DPU) workers, which offer a scalable and cost-effective way to run most jobs. Worker Type Number of Workers Number of DPUs Duration (minutes) Cost at $0.44/DPU-hour 1X (1 DPU) and G.2X The following table shows the results of the benchmark.

Data Lake 100

Data Lake Cost-Benefit Data Integration Data Transformation 100

Cloudera

OCTOBER 11, 2021

They will automatically get the benefits of CDP Shared Data Experience (SDX) with enterprise-grade security and governance. Modak Nabu reliably curates datasets for any line of business and personas, from business analysts to data scientists. Customers using Modak Nabu with CDP today have deployed Data Lakes and.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

AWS Big Data

DECEMBER 21, 2023

The data volume is in double-digit TBs with steady growth as business and data sources evolve. smava’s Data Platform team faced the challenge to deliver data to stakeholders with different SLAs, while maintaining the flexibility to scale up and down while staying cost-efficient.

Data Lake 103

Data Lake Data Warehouse Data-driven B2B 103

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

Cloudera

JUNE 1, 2021

Cloudera will become a private company with the flexibility and resources to accelerate product innovation, cloud transformation and customer growth. These acquisitions usher in a new era of “ self-service ” by automating complex operations so customers can focus on building great data-driven apps instead of managing infrastructure.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

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 106

IoT Data Warehouse Cost-Benefit Reporting 106

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. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

Data Warehouse 104

Data Warehouse Analytics Data Lake Data Science 104

AWS Big Data

DECEMBER 4, 2024

Inspired by these global trends and driven by its own unique challenges, ANZ’s Institutional Division decided to pivot from viewing data as a byproduct of projects to treating it as a valuable product in its own right. For instance, one enhancement involves integrating cross-functional squads to support data literacy.

Metadata 93

Metadata Data Governance Data Quality Data-driven 93

AWS Big Data

AUGUST 1, 2024

These challenges can range from ensuring data quality and integrity during the migration process to addressing technical complexities related to data transformation, schema mapping, performance, and compatibility issues between the source and target data warehouses.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 97

Enterprise Data Warehouse Data Lake Optimization 97

AWS Big Data

AUGUST 19, 2024

We also use Amazon S3 to store AWS Glue scripts, logs, and temporary data generated during the ETL process. This approach offers the following benefits: Enhanced security – By using PrivateLink and VPC endpoints, data transfer between Snowflake and Amazon S3 is secured within the AWS network, reducing exposure to potential security threats.

Analytics 107

Analytics Data-driven Data Integration Data Lake 107

AWS Big Data

FEBRUARY 6, 2023

In the post Introducing the AWS ProServe Hadoop Migration Delivery Kit TCO tool , we introduced the AWS ProServe Hadoop Migration Delivery Kit (HMDK) TCO tool and the benefits of migrating on-premises Hadoop workloads to Amazon EMR. Are any mixed development and operation jobs operating in one cluster? Choose Delete. Choose Delete stack.

Dashboards 83

Dashboards Optimization Data Lake Cost-Benefit 83

AWS Big Data

OCTOBER 27, 2023

AWS Glue , a serverless data integration and extract, transform, and load (ETL) service, has revolutionized this process, making it more accessible and efficient. AWS Glue eliminates complexities and costs, allowing organizations to perform data integration tasks in minutes, boosting efficiency.

Analytics 110

Analytics Visualization Data Integration Cost-Benefit 110

AWS Big Data

FEBRUARY 6, 2023

To solve this, we’re introducing the Hadoop migration assessment Total Cost of Ownership (TCO) tool. The self-serve HMDK TCO tool accelerates the design of new cost-effective Amazon EMR clusters by analyzing the existing Hadoop workload and calculating the total cost of the ownership (TCO) running on the future Amazon EMR system.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 72

Optimization Data Lake Cost-Benefit Reporting 72

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging.

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

Ontotext

FEBRUARY 12, 2024

The data mesh concept will mitigate cognitive overload when building data-driven organizations that require intense technical, domain, and operational knowledge. For many organizations, a centralized data platform will fall short as it gives data teams much less autonomy over managing increasingly diverse and voluminous datasets.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

MARCH 3, 2023

From detailed design to a beta release, Tricentis had customers expecting to consume data from a data lake specific to only their data, and all of the data that had been generated for over a decade. Data export As stated earlier, some customers want to get an export of their test data and create their data lake.

Software 52

Software Data Lake Testing Cost-Benefit 52

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 70

Risk Modeling Management Metadata 70

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

IBM Big Data Hub

JULY 17, 2023

.” Sean Im, CEO, Samsung SDS America “In the field of generative AI and foundation models, watsonx is a platform that will enable us to meet our customers’ requirements in terms of optimization and security, while allowing them to benefit from the dynamism and innovations of the open-source community.”

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Alation

MARCH 22, 2022

So, how can you quickly take advantage of the DataOps opportunity while avoiding the risk and costs of DIY? This platform can be implemented in a cost-effective serverless cloud environment and put to work right away. They can better understand data transformations, checks, and normalization. Alation’s DataOps Role.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

AWS Big Data

APRIL 5, 2023

Showpad also struggled with data quality issues in terms of consistency, ownership, and insufficient data access across its targeted user base due to a complex BI access process, licensing challenges, and insufficient education. The company also used the opportunity to reimagine its data pipeline and architecture.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

CIO Business Intelligence

AUGUST 7, 2024

Now fully deployed, TCS is seeing the benefits. The framework “has revolutionized enterprise API development,” says CIO Milind Wagle, who cites several transformative benefits, including improved speed to market and a two- to threefold improvement in developer productivity when building APIs within industry and Equinix standards.

IT 119

IT Insurance Cost-Benefit Testing 119

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 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 Visualization 52