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 88

Data Architecture Unstructured Data Manufacturing IT 88

CIO Business Intelligence

NOVEMBER 17, 2022

Here are tips from technology resume experts on how to write the ideal resume for chief data officer positions, along with one shining example. Focus on transformation. However, the ability to drive digital technology transformation is going to be the focus,” says Stephen Van Vreede, resume expert at IT Tech Exec.

Data Governance 116

Data Governance Data Transformation Strategy Reporting 116

DataKitchen

JULY 27, 2023

Here are a few examples that we have seen of how this can be done: Batch ETL with Azure Data Factory and Azure Databricks: In this pattern, Azure Data Factory is used to orchestrate and schedule batch ETL processes. Azure Blob Storage serves as the data lake to store raw data. Azure Machine Learning).

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

DECEMBER 6, 2023

As the digital era paves the way for new economic platforms and opportunities, it also leverages the role of cross-industry collaboration, especially in technology. Historically, the technology partner relationship used to be a body count per dollar efficiency ratio, which focuses on getting work done while best optimising the budget.

Digital Transformation 114

Digital Transformation Software Cost-Benefit Manufacturing 114

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 79

Analytics Metrics Visualization Dashboards 79

Analytics Vidhya

JUNE 23, 2022

Introduction to Data Engineering In recent days the consignment of data produced from innumerable sources is drastically increasing day-to-day. So, processing and storing of these data has also become highly strenuous. The post Data Engineering – A Journal with Pragmatic Blueprint appeared first on Analytics Vidhya.

Machine Learning 338

Machine Learning Data Science Publishing Technology 338

Smart Data Collective

OCTOBER 20, 2021

As per the TDWI survey, more than a third (nearly 37%) of people has shown dissatisfaction with their ability to access and integrate complex data streams. Why is Data Integration a Challenge for Enterprises? This speeds up data transformation and decision-making.

Data Integration 122

Data Integration Machine Learning Big Data Data Transformation 122

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 91

Metadata Data Lake Visualization Data Transformation 91

CIO Business Intelligence

JANUARY 24, 2024

These autonomous software agents, working collaboratively in a decentralized fashion, are not just a technological marvel; they are an imperative response to the escalating complexity of today’s challenges. As AI accelerates at a breakneck pace, the urgency to harness the potential of Agent Swarms becomes increasingly apparent.

IoT 105

IoT Machine Learning Optimization Internet of Things 105

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 90

Insurance Strategy Data Governance Data Integration 90

DataKitchen

NOVEMBER 10, 2023

Solutions to Reign in the Chaos Implementing Data Observability Platforms: Tools like DataKitchen’s DataOps Observability provide an overarching view of the entire Data Journey. They enable continuous monitoring of data transformations and integrations, offering invaluable insights into data lineage and changes.

Data Quality 136

Data Quality Testing Data Lake Data Integration 136

CIO Business Intelligence

FEBRUARY 16, 2023

The company’s orthodontics business, for instance, makes heavy use of image processing to the point that unstructured data is growing at a pace of roughly 20% to 25% per month. Advances in imaging technology present Straumann Group with the opportunity to provide its customers with new capabilities to offer their clients.

Unstructured Data 104

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 104

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 95

Analytics Data Lake Metadata Cost-Benefit 95

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. 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

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 Here, it all comes down to the data transformation error rate.

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

OCTOBER 11, 2022

“AI Bench is a set of automated tools and guardrails that help us spin up the right environments in an automated fashion, so our data scientists can quickly begin working in a safe, secure, environment while ensuring regulatory compliance,” said Brian Dummann, AstraZeneca’s Vice President of Insights & Technology Excellence.

Machine Learning 145

Machine Learning Data-driven Testing Data Science 145

Octopai

MARCH 31, 2021

In other words, kind of like Hansel and Gretel in the forest, your data leaves a trail of breadcrumbs – the metadata – to record where it came from and who it really is. So the first step in any data lineage mapping project is to ensure that all of your data transformation processes do in fact accurately record metadata.

Metadata 130

Metadata Data Transformation Business Intelligence Reporting 130

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.

Data Integration 105

Data Integration Data Lake Data Warehouse Software 105

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. When all linked accounts data is collected, the Shared Workflow state machine triggers an AWS Glue job for further data transformation.

Dashboards 97

Dashboards Analytics Metadata Data Warehouse 97

Jet Global

MAY 6, 2024

Despite the transformative potential of AI, a large number of finance teams are hesitating, waiting for this emerging technology to mature before investing. These tools excel at data integration, consolidating information from various financial systems (ERP, CRM, legacy) into a central hub.

Finance 52

Finance Reporting Data Transformation Optimization 52

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 Modeling 130

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

CIO Business Intelligence

JUNE 13, 2022

New technologies hit the market, existing ones evolve, business needs change on a dime, staff comes and goes. Technology has to move much closer to the customer, but there are still intermediaries. CIOs still have interpreters, they have interpreters between the actual users and the technology organization,” he says.

IT 144

IT Digital Transformation Strategy Internet of Things 144

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

CIO Business Intelligence

JANUARY 12, 2023

This has not been helped by the fact that universities have traditionally lagged the private sector in terms of cloud adoption, a key technology enabler for effective data storage and analysis. Comprehensive upskilling programme to overcome data skills gaps.

Data Strategy 87

Data Strategy Strategy IT Consulting 87

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 141

Data Warehouse Digital Transformation Data-driven Reporting 141

erwin

JUNE 29, 2021

From overburdened data operations experts enabling data usage, to end-users struggling to access the data that matters, organizations continue to look for ways to give stakeholders the tools they need to do their jobs more effectively. A key trend proving successful in data empowerment is investing in self-service technology.

Data Governance 64

Data Governance Data-driven Reporting Technology 64

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

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 107

Data Warehouse Testing Data Quality Reporting 107

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. In the inventory management and forecasting solution, AWS Glue is recommended for data transformation.

Forecasting 78

Forecasting Management IoT Data-driven 78

bridgei2i

NOVEMBER 17, 2020

Over time, as technology started entering every business process, the second wave of automation came with technology implementation. Automation through technology had the same outcomes as the first wave though. Automation through technology had the same outcomes as the first wave though. So is technology.

Deep Learning 85

Deep Learning Manufacturing Optimization Data-driven 85

Ontotext

MARCH 20, 2024

Unleashing the Power of Data Connections Zenia Graph isn’t just another data solution company. We are pioneers in knowledge graphs – a revolutionary technology that goes beyond simple data analytics, aggregation, and reporting. Zenia Graph’s Salesforce Accelerator makes this a reality.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

Jen Stirrup

SEPTEMBER 30, 2021

Now that’s done, let’s try and relate it to technology that you already know. If you’ve previously done work in SQL Server Analysis Services, you will know that Analysis Services had data mining functionality. Excel specialists may know that Excel also has a series of Data Mining Add-ins. Business Understanding.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

CIO Business Intelligence

JUNE 29, 2022

But the features in Power BI Premium are now more powerful than the functionality in Azure Analysis Services, so while the service isn’t going away, Microsoft will offer an automated migration tool in the second half of this year for customers who want to move their data models into Power BI instead. Azure Data Factory.

Data Lake 113

Data Lake Analytics Data Warehouse Machine Learning 113

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Key Features: Extensive library of pre-built connectors for diverse data sources.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Anmut

MARCH 24, 2022

We could give many answers, but they all centre on the same root cause: most data leaders focus on flashy technology and symptomatic fixes instead of approaching data transformation in a way that addresses the root causes of data problems and leads to tangible results and business success.

ROI 52

ROI Measurement Data-driven Data Transformation 52