Smart Data Collective

APRIL 14, 2021

Advancement in big data technology has made the world of business even more competitive. The proper use of business intelligence and analytical data is what drives big brands in a competitive market. Business intelligence tools can include data warehousing, data visualizations, dashboards, and reporting.

Business Intelligence 133

Business Intelligence Dashboards Visualization Big Data 133

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.

Dashboards 97

Dashboards Analytics Metadata Data Warehouse 97

CIO Business Intelligence

OCTOBER 26, 2023

This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 125

Business Intelligence Data-driven Statistics Data Warehouse 125

IBM Big Data Hub

DECEMBER 16, 2022

This includes data collection, instrumenting processes and transparent reporting to make needed information available for stakeholders. At IBM, we have an AI Ethics Board that supports a centralized governance, review, and decision-making process for IBM ethics policies, practices, communications, research, products and services.

Uncertainty 114

Uncertainty Metadata Modeling Data Collection 114

Alation

FEBRUARY 20, 2020

Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis. A “big data” revolution has ensued. More than any other advancement in analytic systems over the last 10 years, Hadoop has disrupted data ecosystems.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

FineReport

FEBRUARY 5, 2020

Both the investment community and the IT circle are paying close attention to big data and business intelligence. Metadata management. Users can centrally manage metadata, including searching, extracting, processing, storing, sharing metadata, and publishing metadata externally. Analytics dashboards.

Metadata 98

Metadata Dashboards Informatics Visualization 98

AWS Big Data

FEBRUARY 1, 2024

The Common Crawl corpus contains petabytes of data, regularly collected since 2008, and contains raw webpage data, metadata extracts, and text extracts. In addition to determining which dataset should be used, cleansing and processing the data to the fine-tuning’s specific need is required.

Metadata 99

Metadata Modeling Data Processing Unstructured Data 99

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Conclusion and future work.

Metadata 86

Metadata Data Lake Optimization Strategy 86

Alation

JULY 6, 2021

But first, they need to understand the top challenges to data governance, unique to their organization. Source: Gartner : Adaptive Data and Analytics Governance to Achieve Digital Business Success. As data collection and volume surges, so too does the need for data strategy. Why Do Data Silos Happen?

Data Governance 52

Data Governance Metadata Data Quality Risk 52

Smart Data Collective

APRIL 5, 2022

There are a number of reasons that IBM Watson Studio is a highly popular hardware accelerator among data scientists. It allows data scientists to log, store, share, compare and search important metadata that is used to build models for data science applications. Neptune.ai. Neptune.AI

Cost-Benefit 123

Cost-Benefit Machine Learning Data Science Unstructured Data 123

AWS Big Data

FEBRUARY 21, 2023

Unlike a pure dimensional design, a data vault separates raw and business-generated data and accepts changes from both sources. Data vaults make it easy to maintain data lineage because it includes metadata identifying the source systems. What is a hybrid model?

Data Warehouse 67

Data Warehouse Data Lake Cost-Benefit Modeling 67

Cloudera

NOVEMBER 22, 2021

Explosion of data availability from a variety of sources, including on-premises data stores used by enterprise data warehousing / data lake platforms, data on cloud object stores typically produced by heterogenous, cloud-only processing technologies, or data produced by SaaS applications that have now evolved into distinct platform ecosystems (e.g.,

Data Processing 92

Data Processing Data Warehouse Enterprise Visualization 92

IBM Big Data Hub

FEBRUARY 8, 2023

The IBM AI Governance solution automates across the AI lifecycle from data collection, model building, deploying and monitoring. This comprehensive solution comes without the excessive costs of switching from your current data science platform. Model facts are centralized for AI transparency and explainability.

Risk Management 52

Risk Management Risk Modeling Metadata 52

AWS Big Data

MARCH 13, 2024

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 97

Analytics IoT Metadata Internet of Things 97

Domino Data Lab

OCTOBER 9, 2019

We’ll examine National Oceanic and Atmospheric Administration (NOAA) data management practices which I learned about at their workshop, as a case study in how to handle data collection, dataset stewardship, quality control, analytics, and accountability when the stakes are especially high. Metadata Challenges.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

erwin

DECEMBER 20, 2018

The Top 6 Benefits of Data Governance. www.erwin.com/blog/top-6-benefits-of-data-governance/. GDPR went into effect for businesses trading with the European Union, including hefty fines for noncompliance with its data collection, storage and usage standards. Data Governance 2.0 for Financial Services.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

IBM Big Data Hub

MARCH 29, 2024

Benefits of OpenTelemetry The OpenTelemetry protocol (OTLP) simplifies observability by collecting telemetry data, like metrics, logs and traces, without changing code or metadata. With Turbonomic, you can use Prometheus’ data monitoring tools to automate resourcing decisions based on real-time data collection.

Metrics 78

Metrics Visualization Measurement Optimization 78

IBM Big Data Hub

FEBRUARY 14, 2024

The IBM team is even using generative AI to create synthetic data to build more robust and trustworthy AI models and to stand in for real-world data protected by privacy and copyright laws. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions.

Cost-Benefit 84

Cost-Benefit Insurance Unstructured Data Machine Learning 84

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 61

Data Architecture Data Lake Machine Learning Data Governance 61

Sisense

MAY 18, 2020

In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data. AM: How is data collected to make these recommendations?

Analytics 98

Analytics Digital Transformation Data-driven Sales 98

Alation

JANUARY 17, 2023

Data ingestion/integration services. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? What Are the Benefits of a Modern Data Stack?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

AUGUST 23, 2023

It uses Amazon Simple Storage Service (Amazon S3) as the primary data storage for indexes, adding durability for your data. Collections are able to take advantage of the S3 storage layer to reduce the need for hot storage, and reduce cost, by bringing data into local store when it’s accessed. in OpenSearch Service).

Snapshot 96

Snapshot Dashboards Visualization Metrics 96

Domino Data Lab

JANUARY 21, 2021

First, I load the dataset and do a quick check to see the size of the data we’re working with: Note: the full dataset, with data collection back to 1987, is significantly larger than 300,000 samples. Our customized profile, complete with key metadata and variable descriptions. I’ve turned this on. And the result?

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Alation

FEBRUARY 13, 2020

Today, we’re announcing that Alation has closed a $50 million Series C funding led by Sapphire Ventures, with participation from new investor Salesforce Ventures and our existing investors Costanoa Ventures, DCVC (Data Collective), Harmony Partners and Icon Ventures.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

AWS Big Data

JULY 3, 2023

It provides features such as ACID transactions on top of Amazon S3-based data lakes, schema evolution, partition evolution, and data versioning. With scalable metadata indexing, Apache Iceberg is able to deliver performant queries to a variety of engines such as Spark and Athena by reducing planning time.

Snapshot 86

Snapshot Data Lake Testing Strategy 86

Peter James Thomas

AUGUST 29, 2018

Additionally I have a direct set of reports who drive the standard solutions around tooling, governance, quality, data protection , Data Ethics , Metadata and data glossary and models. Helping organisations become “data-centric” is a key part of what you do.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Maybe they analyzed the metadata from pictures and found that there was a strong correlation between properties that rented often and expensive camera models.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. That was the origin of big data.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Jet Global

MAY 1, 2023

Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. While data exports may satisfy a portion of your customers, there will be many who simply want reports and insights that are available “out of the box.” addresses).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52