CIO Business Intelligence

APRIL 8, 2025

Data is the foundation of innovation, agility and competitive advantage in todays digital economy. As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Data quality is no longer a back-office concern.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

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.

Data Lake 98

Data Lake Data Transformation Data-driven Cost-Benefit 98

O'Reilly on Data

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. Why: Data Makes It Different. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 364

IT Testing Experimentation Software 364

AWS Big Data

JANUARY 27, 2023

To build a data-driven business, it is important to democratize enterprise data assets in a data catalog. With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. GenericInMemoryCatalog stores the catalog data in memory.

Data Lake 87

Data Lake Metadata Business Analysis Data-driven 87

AWS Big Data

DECEMBER 4, 2024

In today’s rapidly evolving financial landscape, data is the bedrock of innovation, enhancing customer and employee experiences and securing a competitive edge. Like many large financial institutions, ANZ Institutional Division operated with siloed data practices and centralized data management teams.

Metadata 105

Metadata Data Governance Data Quality Data-driven 105

AWS Big Data

DECEMBER 16, 2024

The need to integrate diverse data sources has grown exponentially, but there are several common challenges when integrating and analyzing data from multiple sources, services, and applications. First, you need to create and maintain independent connections to the same data source for different services.

Visualization 92

Visualization Data Processing Testing Publishing 92

CIO Business Intelligence

JUNE 29, 2022

If you can’t make sense of your business data, you’re effectively flying blind. 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. Azure Data Factory.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

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 111

Metadata Data Lake Visualization Data Quality 111

AWS Big Data

DECEMBER 21, 2023

This is a guest post co-written by Alex Naumov, Principal Data Architect at smava. smava believes in and takes advantage of data-driven decisions in order to become the market leader. smava believes in and takes advantage of data-driven decisions in order to become the market leader.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

AWS Big Data

AUGUST 9, 2024

As businesses strive to make informed decisions, the amount of data being generated and required for analysis is growing exponentially. This trend is no exception for Dafiti , an ecommerce company that recognizes the importance of using data to drive strategic decision-making processes. We started with 115 dc2.large

Data Lake 111

Data Lake Analytics Data Warehouse Data-driven 111

AWS Big Data

APRIL 26, 2023

Additionally, this forecasting system needs to provide data enrichment steps including byproducts, serve as the master data around the semiconductor management, and enable further use cases at the BMW Group. To enable this use case, we used the BMW Group’s cloud-native data platform called the Cloud Data Hub.

Forecasting 144

Forecasting Manufacturing Data Lake Big Data 144

Ontotext

FEBRUARY 12, 2024

In the final part of this three-part series, we’ll explore ho w data mesh bolsters performance and helps organizations and data teams work more effectively. Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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 116

Data Lake Snapshot Big Data Data-driven 116

CIO Business Intelligence

OCTOBER 11, 2022

To accelerate growth through innovation, the company is expanding its use of data science and artificial intelligence (AI) across the business to improve patient outcomes. . This initiative alone has generated an explosion in the quantity and complexity of data the company collects, stores, and analyzes for insights. . “We

Machine Learning 145

Machine Learning Data Science Data-driven Testing 145

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

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.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

AWS Big Data

APRIL 11, 2023

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. To take advantage of this data and build an effective inventory management and forecasting solution, retailers can use a range of AWS services.

Forecasting 98

Forecasting Management IoT Data-driven 98

Cloudera

JUNE 30, 2022

We are excited to announce the general availability of Apache Iceberg in Cloudera Data Platform (CDP). These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

AWS Big Data

AUGUST 19, 2024

In today’s data-driven world, the ability to seamlessly integrate and utilize diverse data sources is critical for gaining actionable insights and driving innovation. Use case Consider a large ecommerce company that relies heavily on data-driven insights to optimize its operations, marketing strategies, and customer experiences.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

IBM Big Data Hub

JUNE 15, 2023

There’s no debate that the volume and variety of data is exploding and that the associated costs are rising rapidly. The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Enter the open data lakehouse.

Data Warehouse 86

Data Warehouse Data Lake Optimization Data-driven 86

Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). The Open Data Lakehouse . Introduction.

Data Warehouse 81

Data Warehouse Data Transformation Machine Learning Data Lake 81

AWS Big Data

AUGUST 13, 2024

In today’s data-driven world, seamless integration and transformation of data across diverse sources into actionable insights is paramount. With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog.

Data Processing 115

Data Processing Visualization Data Lake Data Processing 115

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. This native feature of Amazon Redshift uses massive parallel processing (MPP) to load objects directly from data sources into Redshift tables.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

Cloudera

JUNE 1, 2021

This means we can double down on our strategy – continuing to win the Hybrid Data Cloud battle in the IT department AND building new, easy-to-use cloud solutions for the line of business. It also means we can complete our business transformation with the systems, processes and people that support a new operating model. .

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

AWS Big Data

NOVEMBER 7, 2023

The most impactful data-driven insights come from connecting the dots between all your data sources—across departments, services, on-premises tools, and third-party applications. But typically, connecting data requires complex extract, transform, and load (ETL) pipelines, taking hours or days.

Dashboards 80

Dashboards Data-driven Data Integration Data Lake 80

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. It is too expensive.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 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 124

Analytics Visualization Data Integration Cost-Benefit 124

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. 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. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

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

Alation

MARCH 22, 2022

Data people face a challenge. They must put high-quality data into the hands of users as efficiently as possible. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

AWS Big Data

APRIL 5, 2023

In 2021, Showpad set forth the vision to use the power of data to unlock innovations and drive business decisions across its organization. In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers. Showpad migrated over 70 dashboards with over 1,000 visuals.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

CIO Business Intelligence

AUGUST 7, 2024

Its AI/ML-driven predictive analysis enhanced proactive threat hunting and phishing investigations as well as automated case management for swift threat identification. Options included hosting a secondary data center, outsourcing business continuity to a vendor, and establishing private cloud solutions.

IT 119

IT Insurance Cost-Benefit Testing 119

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. 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