CIO Business Intelligence

FEBRUARY 20, 2024

Manufacturers have long held a data-driven vision for the future of their industry. It’s one where near real-time data flows seamlessly between IT and operational technology (OT) systems. Denso uses AI to verify the structuring of unstructured data from across its organisation.

Data Architecture 75

Data Architecture Unstructured Data Manufacturing IT 75

AWS Big Data

OCTOBER 11, 2023

The lift and shift migration approach is limited in its ability to transform businesses because it relies on outdated, legacy technologies and architectures that limit flexibility and slow down productivity. It shows a call center streaming data source that sends the latest call center feed in every 15 seconds.

Management 105

Management Metadata Analytics Dashboards 105

erwin

APRIL 16, 2024

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

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 83

Analytics Data Lake Metadata Cost-Benefit 83

CIO Business Intelligence

APRIL 30, 2024

Together the technologies aim to help business users and “novice” data analysts explore their data and gain insights without having to resort to data experts. This is really empowering everyone to be a data expert,” Maxon said.

Analytics 67

Analytics Metrics Visualization Dashboards 67

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset. You might notice that this differs slightly from traditional ETL.

Dashboards 96

Dashboards Analytics Metadata Data Warehouse 96

AWS Big Data

APRIL 2, 2024

You can see the decompressed data has metadata information such as logGroup , logStream , and subscriptionFilters , and the actual data is included within the message field under logEvents (the following example shows an example of CloudTrail events in the CloudWatch Logs). You can connect with Ranjit on LinkedIn.

Metadata 86

Metadata Marketing Analytics Data Transformation 86

CIO Business Intelligence

MARCH 4, 2024

These domain data leaders often cite the diminishing returns and significant effort of central data team engagement. Additionally, data silos and fragmentation often occur inorganically as in the case of merger or acquisition scenarios.

Insurance 77

Insurance Strategy Data Governance Data Integration 77

datapine

SEPTEMBER 29, 2022

Today most of a company’s operations and strategic decisions heavily rely on data, so the importance of quality is even higher. And indeed, low-quality data is the leading cause of failure for advanced data and technology initiatives, to the tune of $9.7 2 – Data profiling. 1 – The people.

Data Quality 241

Data Quality Metrics Data-driven Management 241

IBM Big Data Hub

JANUARY 9, 2024

The emergence of generative AI prompted several prominent companies to restrict its use because of the mishandling of sensitive internal data. According to CNN, some companies imposed internal bans on generative AI tools while they seek to better understand the technology and many have also blocked the use of internal ChatGPT.

Enterprise 73

Enterprise Data Integration Data Quality Contextual Data 73

IBM Big Data Hub

JULY 5, 2023

It gained rapid popularity given its support for data transformations, streaming and SQL. But it never co-existed amicably within existing data lake environments. Fast forward almost 15 years and reality has clearly set in on the trade-offs and compromises this technology entailed.

Data Lake 61

Data Lake Metadata Cost-Benefit Data Warehouse 61

Alation

AUGUST 11, 2022

In the technology industry, even the most incremental trends often get framed in next-generation terminology. DataOps sprung up to connect data sources to data consumers. The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Tools became stacks.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 71

Risk Modeling Management Metadata 71

erwin

APRIL 29, 2020

Tracing the source of data is an arduous task. Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Who are the data owners? Data Quality.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

AWS Big Data

JANUARY 27, 2023

With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. 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. Refer to Catalogs for more information.

Data Lake 62

Data Lake Metadata Business Analysis Data-driven 62

Alation

MARCH 22, 2022

In fact, DataOps (and its underlying foundation, Data Fabric ), has ranked as a top area of inquiry and interest with analysts over the past twelve months. DataOps requires an array of technology to automate the design, development, deployment, and management of data delivery, with governance sprinkled on for good measure.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 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

Octopai

NOVEMBER 13, 2022

A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting. In the ideal modern data stack, it should be easy to connect these components and no big deal to switch one component out for another.

Enterprise 77

Enterprise Data Warehouse Reporting Metadata 77

Ontotext

FEBRUARY 12, 2024

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. However, data mesh is not about introducing new technologies.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

erwin

SEPTEMBER 17, 2020

Speed and faster time to market is a driving force behind most organizations’ efforts with data lineage automation. More work can be done when you are not waiting on someone to manually process data or forms. Business terms and data policies should be implemented through standardized and documented business rules.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

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 77

Cost-Benefit Metadata Optimization Management 77

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. This is something that you can learn more about in just about any technology blog.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

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. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

JANUARY 18, 2023

This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems. The data warehouse storage layer is removed from lakehouse architectures. Instead, continuous data transformation is performed within the BLOB storage. All phases of the data-information lifecycle.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

JULY 20, 2023

Orca connects to your environment in minutes with patented SideScanning technology to provide complete coverage across vulnerabilities, malware, misconfigurations, lateral movement risk, weak and leaked passwords, overly permissive identities, and more. In addition, we describe the Orca Platform architecture and the technologies used.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 92

Data Lake Cost-Benefit Data-driven Dashboards 92

erwin

MARCH 4, 2021

However, while digital transformation and other data-driven initiatives are desired outcomes, few organizations know what data they have or where it is, and they struggle to integrate known data in various formats and numerous systems – especially if they don’t have a way to automate those processes.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Ontotext

NOVEMBER 18, 2021

Through this series of blog posts, we’ll discuss how to best scale and branch out an analytics solution using a knowledge graph technology stack. OntoRefine is a data transformation tool that lets you unite plenty of data formats and get them into your triplestore. How to scale properly? Luckily, we are here to help.

Visualization 98

Visualization Reporting Metadata Enterprise 98

IBM Big Data Hub

JULY 17, 2023

foundation models to help users discover, augment, and enrich data with natural language. Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance.

Visualization 97

Visualization Dashboards Data-driven Gap analysis 97

AWS Big Data

MARCH 15, 2023

The API retrieves data at runtime from an Amazon Aurora PostgreSQL-Compatible Edition database for end-user consumption. To populate the database, the Infomedia team developed a data pipeline using Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue for data transformations, and Apache Hudi for CDC and record-level updates.

Cost-Benefit 67

Cost-Benefit Data Processing Optimization Data-driven 67

Cloudera

NOVEMBER 22, 2021

Open source frameworks such as Apache Impala, Apache Hive and Apache Spark offer a highly scalable programming model that is capable of processing massive volumes of structured and unstructured data by means of parallel execution on a large number of commodity computing nodes. . As a result, alternative data integration technologies (e.g.,

Data Processing 92

Data Processing Data Warehouse Enterprise Visualization 92

AWS Big Data

NOVEMBER 16, 2023

Data Vault 2.0 allows for the following: Agile data warehouse development Parallel data ingestion A scalable approach to handle multiple data sources even on the same entity A high level of automation Historization Full lineage support However, Data Vault 2.0

Enterprise 85

Enterprise Data Warehouse Data Lake Optimization 85

Alation

JANUARY 17, 2023

The modern data stack started to gain popularity in the early 2010s, as companies began to realize the benefits of big data. Most importantly, cloud computing has gotten much faster and cheaper, emerging as the core technology driving the development of the modern data stack. How Can I Build a Modern Data Stack?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

OCTOBER 18, 2023

To look for fraud, market manipulation, insider trading, and abuse, FINRA’s technology group has developed a robust set of big data tools in the AWS Cloud to support these activities. Melody Yang is a Senior Big Data Solutions Architect for Amazon EMR at AWS.

Big Data 81

Big Data Data Processing Interactive Testing 81

Jet Global

MARCH 14, 2024

With the right technology solutions in place, you can stay ahead of the proverbial learning curve and experience the full potential of your Fabric integration from day one. Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric. Or does it?

Analytics 52

Analytics Management Reporting Enterprise 52

Jet Global

MAY 1, 2023

BI is a set of independent systems (technologies, processes, people, etc.) that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint. And Manufacturing and Technology, both 11.6 It’s all about context. Financial Services represent 13.0

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52