datapine

APRIL 15, 2020

To make sure your BI and agile data analytics methodologies are successfully implemented and will deliver actual business value, here we present some extra tips that will ensure you stay on track and don’t forget any important point in the process, starting with the stakeholders. Active stakeholder engagement.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

AWS Big Data

SEPTEMBER 12, 2024

On the importance of company data for generative AI, McKinsey stated that “If your data isn’t ready for generative AI, your business isn’t ready for generative AI.” In this post, we present a framework to implement generative AI applications enriched and differentiated with your data.

Management 104

Management Analytics Data Lake Interactive 104

AWS Big Data

MARCH 1, 2023

Finding similar columns in a data lake has important applications in data cleaning and annotation, schema matching, data discovery, and analytics across multiple data sources. In this example, we searched for columns in our data lake that have similar Column Names ( payload type ) to district ( payload ).

Data Lake 105

Data Lake Deep Learning Interactive Machine Learning 105

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 119

Data Lake Data Warehouse Management Risk 119

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 98

Data Lake Data Governance Data Architecture Machine Learning 98

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 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

CIO Business Intelligence

SEPTEMBER 8, 2022

The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data. But poor data quality, siloed data, entrenched processes, and cultural resistance often present roadblocks to using data to speed up decision making and innovation.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Collection 122

Cloudera

DECEMBER 1, 2022

Data observability provides insight into the condition and evolution of the data resources from source through the delivery of the data products. Barr Moses of Monte Carlo presents it as a combination of data flow, data quality, data governance, and data lineage.

Data Quality 84

Data Quality Metrics Data Lake Statistics 84

AWS Big Data

DECEMBER 19, 2024

Data has become an invaluable asset for businesses, offering critical insights to drive strategic decision-making and operational optimization. From establishing an enterprise-wide data inventory and improving data discoverability, to enabling decentralized data sharing and governance, Amazon DataZone has been a game changer for HEMA.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI).

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

CIO Business Intelligence

APRIL 4, 2024

Access to digitized records as well as analytics and AI tools gives public defenders like Cox the time required to present clients’ cases more thoroughly and build a better defense, which in Johnny’s case led to a treatment program instead of prison time.

Digital Transformation 111

Digital Transformation Data Lake ROI Modeling 111

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake.

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

CIO Business Intelligence

NOVEMBER 28, 2023

With each game release and update, the amount of unstructured data being processed grows exponentially, Konoval says. This volume of data poses serious challenges in terms of storage and efficient processing,” he says. To address this problem RetroStyle Games invested in data lakes. Quality is job one.

Unstructured Data 130

Unstructured Data Data-driven Visualization Data Quality 130

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. This process has been scheduled to run daily, ensuring a consistent batch of fresh data for analysis. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

AWS Big Data

FEBRUARY 8, 2023

It’s common to ingest multiple data sources into Amazon Redshift to perform analytics. Often, each data source will have its own processes of creating and maintaining data, which can lead to data quality challenges within and across sources. all URIDs that have are present).

Data Quality 98

Data Quality Testing Data Warehouse Unstructured Data 98

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 111

Enterprise Data Warehouse Snapshot Cost-Benefit 111

CIO Business Intelligence

JULY 31, 2024

We also have a blended architecture of deep process capabilities in our SAP system and decision-making capabilities in our Microsoft tools, and a great base of information in our integrated data hub, or data lake, which is all Microsoft-based. That’s what we’re running our AI and our machine learning against.

Manufacturing 122

Manufacturing Cost-Benefit Digital Transformation Forecasting 122

erwin

AUGUST 31, 2023

Improved Decision Making : Well-modeled data provides insights that drive informed decision-making across various business domains, resulting in enhanced strategic planning. Reduced Data Redundancy : By eliminating data duplication, it optimizes storage and enhances data quality, reducing errors and discrepancies.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Analytics 52

Alation

JULY 19, 2022

Modern data catalogs also facilitate data quality checks. Historically restricted to the purview of data engineers, data quality information is essential for all user groups to see. Cataloging data science projects in this way is critical to helping them generate value for the company.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Ontotext

FEBRUARY 12, 2024

It proposes a technological, architectural, and organizational approach to solving data management problems by breaking up the monolithic data platform and de-centralizing data management across different domain teams and services. Some examples of data products are data sets, tables, machine learning models, and APIs.

IT 64

IT Metadata Data Quality Data Lake 64

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. It consists of full-day and intraday tables.

Analytics 59

Analytics Data Lake Testing Optimization 59

AWS Big Data

DECEMBER 9, 2024

Equally crucial is the ability to segregate and audit problematic data, not just for maintaining data integrity, but also for regulatory compliance, error analysis, and potential data recovery. One of its key features is the ability to manage data using branches.

Data Quality 126

Data Quality Publishing Snapshot Data Lake 126

CIO Business Intelligence

AUGUST 14, 2024

Start where your data is Using your own enterprise data is the major differentiator from open access gen AI chat tools, so it makes sense to start with the provider already hosting your enterprise data. Organizations with experience building enterprise data lakes connecting to many different data sources have AI advantages.

Enterprise 136

Enterprise Cost-Benefit Experimentation Modeling 136

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Peter James Thomas

MAY 3, 2019

Control of Data to ensure it is Fit-for-Purpose. This refers to a wide range of activities from Data Governance to Data Management to Data Quality improvement and indeed related concepts such as Master Data Management. When I first started focussing on the data arena, Data Warehouses were state of the art.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

IBM Big Data Hub

JULY 27, 2023

Data quality strongly impacts the quality and usefulness of content produced by an AI model, underscoring the significance of addressing data challenges. It provides the combination of data lake flexibility and data warehouse performance to help to scale AI.

Management 54

Management Enterprise Modeling Data Quality 54

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

Alation

AUGUST 11, 2022

Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. So we have to be very careful about giving the domains the right and authority to fix data quality. Let’s take data privacy as an example.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Alation

NOVEMBER 28, 2022

Sathish Raju, cofounder & CTO, Kloudio and senior director of engineering, Alation: This presents challenges for both business users and data teams. It’s impossible for data teams to assure the data quality of such spreadsheets and govern them all effectively.

Metadata 52

Metadata Enterprise Cost-Benefit Finance 52

FineReport

MARCH 24, 2024

Daily, data analysts engage in various tasks tailored to their organization’s needs, including identifying efficiency improvements, conducting sector and competitor benchmarking, and implementing tools for data validation. Showcase relevant work experiences, even if they may not directly align with the internship role.

Statistics 52

Statistics Data mining Visualization Sales 52

CIO Business Intelligence

MARCH 18, 2024

We are proceeding cautiously because the rise of LLMs [large language models] presents a new level of data security risk,” he says. “We This ensures that none of our sensitive data and intellectual property are availed to an outside provider.” AI tools rely on the data in use in these solutions.

Risk 133

Risk Cost-Benefit Data Processing Testing 133

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

datapine

AUGUST 29, 2022

Each of the three parts starts with chapters that are theoretical and finishes with more practical ones to make sense of all the concepts and knowledge previously presented, which is something that readers really enjoy about Nathan Marz’s work. – Eric Siegel, author, and founder of Predictive Analytics World.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

JANUARY 16, 2025

The mega-vendor era By 2020, the basis of competition for what are now referred to as mega-vendors was interoperability, automation and intra-ecosystem participation and unlocking access to data to drive business capabilities, value and manage risk.

Enterprise 105

Enterprise Digital Transformation Scorecard Interactive 105