CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

Analytics Vidhya

FEBRUARY 23, 2020

Overview What is sports analytics? What are the different use cases of sports analytics? We answer these questions here Understand how sports analytics can. The post Sports Analytics – Generating Actionable Insights using Cricket Commentary appeared first on Analytics Vidhya.

Analytics 317

Analytics Unstructured Data Visualization Data Analytics 317

AWS Big Data

MARCH 7, 2024

You can take all your data from various silos, aggregate that data in your data lake, and perform analytics and machine learning (ML) directly on top of that data. You can also store other data in purpose-built data stores to analyze and get fast insights from both structured and unstructured data.

Data Lake 109

Data Lake Analytics Dashboards Metrics 109

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 108

Analytics IoT Data-driven Snapshot 108

Cloudera

APRIL 20, 2021

What is Streaming Analytics? Streaming Analytics is a type of data analysis that processes data streams for real-time analytics. It continuously processes data from multiple streams and performs simple calculations to complex event processing for delivering sophisticated use cases.

Analytics 95

Analytics Unstructured Data IoT Visualization 95

FineReport

JULY 28, 2021

If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. What is Data Science? Typical tools for data science: SAS, Python, R.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Analytics Vidhya

APRIL 26, 2023

DocVQA(Document Visual Question Answering) is a cutting-edge approach combining […] The post Document Information Extraction Using Pix2Struct appeared first on Analytics Vidhya. The extracted information can be used for various purposes, such as analysis and classification.

Structured Data 278

Structured Data Visualization Reporting Analytics 278

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

Smarten

JUNE 10, 2022

Why You Need Both BI Tools and Augmented Analytics and What to Consider When Selecting a Vendor ! According to a West Monroe Partners’ survey, 68% of business and technology leaders surveyed don’t believe their competitors are leveraging data successfully. Predictive Modeling to support business needs, forecast, and test theories.

Slice and Dice 52

Slice and Dice Analytics Key Performance Indicator Business Intelligence 52

BizAcuity

OCTOBER 21, 2019

Over the decade’s Hospitality Industry wings expand to the new horizon due to the widespread usage of mobiles which allows customers to plan the vacation & visualize the ambiance at their fingertips. Text analytics helps to draw the insights from the unstructured data. . The way forward.

Analytics 73

Analytics Unstructured Data Data mining Structured Data 73

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. In some ways, the data architect is an advanced data engineer.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

AUGUST 3, 2023

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need. Then we can query the data with Amazon Athena visualize it in Amazon QuickSight.

Data Lake 76

Data Lake Visualization Dashboards Insurance 76

CIO Business Intelligence

AUGUST 9, 2023

Unstructured data needs for generative AI Generative AI architecture and storage solutions are a textbook case of “what got you here won’t get you there.” In other words, storage platforms must be aligned with the realities of unstructured data and the emerging needs of generative AI. Learn more here.

Unstructured Data 98

Unstructured Data Modeling Data Architecture Enterprise 98

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new. Inability to get data quickly.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

CIO Business Intelligence

APRIL 22, 2022

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science gives the data collected by an organization a purpose. Data science vs. data analytics.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

CIO Business Intelligence

NOVEMBER 28, 2023

With organizations seeking to become more data-driven with business decisions, IT leaders must devise data strategies gear toward creating value from data no matter where — or in what form — it resides. Unstructured data resources can be extremely valuable for gaining business insights and solving problems.

Unstructured Data 130

Unstructured Data Data-driven Visualization Data Quality 130

datapine

JUNE 5, 2019

Let’s kick things off by asking the question: what is a data dashboard? Exclusive Bonus Content: Ready to make analytics straightforward? Learn all about data dashboards with our executive bite-sized summary! What Is A Data Dashboard? Or in other words, delve into the heart of the dashboard meaning. click to enlarge**.

Dashboards 316

Dashboards KPI Sales Visualization 316

FineReport

APRIL 26, 2023

With the right Big Data Tools and techniques, organizations can leverage Big Data to gain valuable insights that can inform business decisions and drive growth. What is Big Data? What is Big Data? It is an ever-expanding collection of diverse and complex data that is growing exponentially.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

BizAcuity

OCTOBER 21, 2019

Over the decade’s Hospitality Industry wings expand to the new horizon due to the widespread usage of mobiles which allows customers to plan the vacation & visualize the ambiance at their fingertips. Text analytics helps to draw the insights from the unstructured data. DECODING ONLINE REVIEWS THROUGH ANALYTICS.

Analytics 40

Analytics Unstructured Data Data mining Structured Data 40

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

FineReport

JULY 1, 2021

If you have never heard of BI, I suggest you read these two articles, one on BI and analytics and one on BI reporting , to build your background knowledge. BI technology is a series of technologies that can handle a large amount of structured and sometimes unstructured data. Data querying & discovery.

Business Intelligence 98

Business Intelligence Technology Data Warehouse Dashboards 98

IBM Big Data Hub

OCTOBER 12, 2022

To identify and distill the insights locked inside this sea of “unstructured” data, ESPN collaborated with IBM to teach Watson the language of football. It lets a fantasy owner visualize the risk-and-reward scenarios, see trends over time and field a more competitive team. Not anymore. Encouraging trades and transactions.

Unstructured Data 86

Unstructured Data Consulting Statistics Data-driven 86

Smarten

MAY 17, 2017

If you are considering a Business Intelligence solution, you ought to give some consideration to the concept of Smart Data Visualization and review your prospective solution to determine its capabilities in that regard. How do users perceive and use data? How do formats and reporting affect a user’s understanding of data?

Visualization 40

Visualization Business Intelligence Unstructured Data Interactive 40

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. Exclusive Bonus Content: Download Our Free Data & Science Checklist! provides the user with visualizations, code editor, and debugging. Let’s get started.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

bridgei2i

SEPTEMBER 23, 2020

She further explains how the traditional BI systems which offers data visualization and building data lakes of structured and unstructured data, compliant with KPIs and analytics infrastructure may not be adequate to handle the data explosion.

Enterprise 97

Enterprise Unstructured Data Data Lake Digital Transformation 97

Analytics Vidhya

APRIL 26, 2024

By employing invertible augmentation techniques and probabilistic application, […] The post How Data Efficient GANs Generate Images of Cats and Dogs? appeared first on Analytics Vidhya.

Modeling 266

Modeling Analytics Unstructured Data Deep Learning 266

Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

Experimentation 83

Experimentation Data Warehouse Dashboards Visualization 83

Smart Data Collective

APRIL 5, 2022

This feature helps automate many parts of the data preparation and data model development process. This significantly reduces the amount of time needed to engage in data science tasks. A text analytics interface that helps derive actionable insights from unstructured data sets.

Cost-Benefit 123

Cost-Benefit Machine Learning Data Science Unstructured Data 123

erwin

JANUARY 9, 2020

They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

Sisense

OCTOBER 6, 2020

As quantitative data is always numeric, it’s relatively straightforward to put it in order, manage it, analyze it, visualize it, and do calculations with it. Spreadsheet software like Excel, Google Sheets, or traditional database management systems all mainly deal with quantitative data. Why is quantitative data important?

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

FEBRUARY 14, 2024

Creative AI use cases Create with generative AI Generative AI tools such as ChatGPT, Bard and DeepAI rely on limited memory AI capabilities to predict the next word, phrase or visual element within the content it’s generating. Generative AI can produce high-quality text, images and other content based on the data used for training.

Cost-Benefit 87

Cost-Benefit Insurance Unstructured Data Machine Learning 87

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Deploying Data Lakes in the cloud. Possibilities with Data Lakes.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

AWS Big Data

MARCH 25, 2024

This data store provides your organization with the holistic customer records view that is needed for operational efficiency of RAG-based generative AI applications. For building such a data store, an unstructured data store would be best. This is typically unstructured data and is updated in a non-incremental fashion.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

CIO Business Intelligence

OCTOBER 3, 2023

Intelligent document processing: uses artificial intelligence and machine learning techniques to automate the processing of documents and unstructured data. Skill gap: hyperautomation requires a diverse skill set that includes process analysis, data analytics, AI, RPA and more.

Cost-Benefit 122

Cost-Benefit Machine Learning Interactive Software 122

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

CIO Business Intelligence

JUNE 28, 2023

The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace. The team leaned on data scientists and bio scientists for expert support. That, in turn, led to a slew of manual processes to make descriptive analysis of the test results.

Digital Transformation 104

Digital Transformation Cost-Benefit Informatics Data mining 104