FineReport

APRIL 26, 2023

This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. 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.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Smart Data Collective

SEPTEMBER 26, 2019

The big data market is expected to be worth $189 billion by the end of this year. A number of factors are driving growth in big data. Demand for big data is part of the reason for the growth, but the fact that big data technology is evolving is another. Unstructured. Structured.

Big Data 80

Big Data Software Unstructured Data Data Integration 80

AWS Big Data

FEBRUARY 29, 2024

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

Data Governance 97

Data Governance Unstructured Data Metadata Data Lake 97

Smart Data Collective

JUNE 7, 2019

This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. Read this article as we’ll tackle what big data and stream processing are. We’ll also deal with how big data stream processing can help new emerging markets in the world.

Big Data 81

Big Data Marketing Cost-Benefit Unstructured Data 81

IBM Big Data Hub

NOVEMBER 29, 2023

Non-symbolic AI can be useful for transforming unstructured data into organized, meaningful information. This helps to simplify data analysis and enable informed decision-making. Events as fuel for AI Models: Artificial intelligence models rely on big data to refine the effectiveness of their capabilities.

Unstructured Data 85

Unstructured Data Data-driven ROI Machine Learning 85

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Instead, what we really need is for our business to run at the speed of data.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

Sisense

MARCH 20, 2019

To do that, a data engineer needs to be skilled in a variety of platforms and languages. In our never-ending quest to make BI better, we took it upon ourselves to list the skills and tools every data engineer needs to tackle the ever-growing pile of Big Data that every company faces today. Python and R. Machine Learning.

Big Data 72

Big Data Machine Learning Data Warehouse Unstructured Data 72

Smart Data Collective

DECEMBER 21, 2020

We previously talked about the benefits of data analytics in the insurance industry. One report found that big data vendors will generate over $2.4 Key benefits of AI include recognizing speech, identifying objects in an image, and analyzing natural or unstructured data forms. Capturing data from documents.

Insurance 134

Insurance Cost-Benefit Big Data Unstructured Data 134

Smart Data Collective

SEPTEMBER 26, 2021

Data mining and knowledge go hand in hand, providing insightful information to create applications that can make predictions, identify patterns, and, last but not least, facilitate decision-making. Working with massive structured and unstructured data sets can turn out to be complicated. A document is susceptible to change.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

CIO Business Intelligence

OCTOBER 13, 2023

Cloud data architect: The cloud data architect designs and implements data architecture for cloud-based platforms such as AWS, Azure, and Google Cloud Platform. Data security architect: The data security architect works closely with security teams and IT teams to design data security architectures.

Data Architecture 121

Data Architecture Data Warehouse Statistics Visualization 121

Smart Data Collective

MARCH 16, 2020

He should elaborate more on the benefits of big data and deep learning. A lot of big data experts argue that deep learning is key to controlling costs. Health IT Analytics wrote an article on the cost benefits of using big data in healthcare. This will be essential for all countries.

Deep Learning 78

Deep Learning Unstructured Data Cost-Benefit Big Data 78

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. A modern ILM approach helps CIOs and their teams align processes to business objectives and regulatory requirements.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

AWS Big Data

MARCH 25, 2024

A RAG-based generative AI application can only produce generic responses based on its training data and the relevant documents in the knowledge base. For example, Amazon DynamoDB provides a feature for streaming CDC data to Amazon DynamoDB Streams or Kinesis Data Streams.

Data Lake 91

Data Lake Unstructured Data Management Modeling 91

IBM Big Data Hub

AUGUST 22, 2023

Digital twins and integrated data For the presentation layer, you can leverage various capabilities, such as 3D modeling, augmented reality and various predictive model-based health scores and criticality indices. Field services.

Unstructured Data 74

Unstructured Data Consulting Visualization IoT 74

Sisense

MAY 26, 2020

In this post, we’ll discuss these challenges in detail and include some tips and tricks to help you handle text data more easily. Unstructured data and Big Data. Most common challenges we face in NLP are around unstructured data and Big Data. is “big” and highly unstructured.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

IBM Big Data Hub

AUGUST 17, 2023

It will help them operationalize and automate governance of their models to ensure responsible, transparent and explainable AI workflows, identify and mitigate bias and drift, capture and document model metadata and foster a collaborative environment. million data points are captured, drawn from every shot of every match.

Unstructured Data 90

Unstructured Data Statistics Consulting Enterprise 90

Smart Data Collective

AUGUST 30, 2022

Centralized data storage. For example, e-mail messages and documents are stored in the cloud, giving users access to their data from any location. Information is encrypted and stored on firewalls or protected by redundancy and many other security methods to ensure data safety. Big data analytics.

Technology 133

Technology Enterprise Cost-Benefit Testing 133

IBM Big Data Hub

DECEMBER 1, 2023

To achieve digital transformation with AI, insurance companies need to get a good understanding of structured and unstructured data, organize it, manage it in a secure manner (while complying with industry regulations) and enable instant access to the “right” data.

Insurance 98

Insurance Digital Transformation Unstructured Data Risk 98

IBM Big Data Hub

SEPTEMBER 7, 2023

After a score is assigned to each sentence in a document, analytics are run over the sentences and scores to explore the distribution, which determines the percentage of sentences for filtering. Besides this, we apply a wide range of other quality measures.

Modeling 102

Modeling Risk Unstructured Data Enterprise 102

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

Smart Data Collective

NOVEMBER 25, 2019

Just as companies are becoming more aware of the value of data, so are hackers — and as a result, the frequency and cost of data breaches are beginning to skyrocket. In the future, companies that come to rely on these new data sources will also need to protect that data — or risk the consequences.

Business Intelligence 101

Business Intelligence Predictive Analytics Data Collection Internet of Things 101

Cloudera

JUNE 4, 2018

That’s the equivalent of 1 petabyte ( ComputerWeekly ) – the amount of unstructured data available within our large pharmaceutical client’s business. Then imagine the insights that are locked in that massive amount of data. Nguyen, Accenture & Mitch Gomulinski, Cloudera.

Unstructured Data 46

Unstructured Data Metadata Big Data Enterprise 46

AWS Big Data

OCTOBER 20, 2023

We’ve seen a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3. Learn more in README.

Data Lake 86

Data Lake Big Data Consulting Data Warehouse 86

Sisense

JULY 23, 2021

At the Information, Knowledge, and Games Learning (IKL) unit, we anticipate collecting about 1TB of data from primary sources. This analytics engine will process both structured and unstructured data. “We

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

O'Reilly on Data

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Machine Learning 243

Machine Learning Testing Modeling Cost-Benefit 243

IBM Big Data Hub

DECEMBER 4, 2023

The most common insurance use cases include optimizing processes that require processing large documents and large blocks of text or images. Customer engagement Providing insurance coverage involves working with numerous documents. IBM works with several insurance companies to identify high-value opportunities for using generative AI.

Insurance 54

Insurance Digital Transformation Risk Management Interactive 54

Cloudera

NOVEMBER 18, 2021

The variety of formats, unstructured nature, and dispersed location of these documents present several challenges for critical business decisions. To enable faster and easier access to millions of documents, ExxonMobil combined domain specific knowledge and a combination of Cloudera tools with cloud services.

Data Lake 76

Data Lake Cost-Benefit Digital Transformation Risk 76

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 85

Big Data Software Consulting Unstructured Data 85

IBM Big Data Hub

AUGUST 28, 2023

These are two common methods for text representation: Bag-of-words (BoW): BoW represents text as a collection of unique words in a text document. Term frequency-inverse document frequency (TF-IDF): TF-IDF calculates the importance of each word in a document based on its frequency or rarity across the entire dataset.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

erwin

JANUARY 17, 2020

Organizations that adopt the Any 2 approach can expect greater consistency, clarity and artifact reuse across large-scale data integration, master data management, metadata management, Big Data and business intelligence/analytics initiatives. The Advantages of NoSQL Data Modeling. What is Data Modeling?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

Cloudera

OCTOBER 28, 2021

The German underwriters analyzed historical data such as weather, location, breed, type of crop, and a farmer’s experience to assess risk, underwrite and set price exposures. In this way, the Commercial Lines segment of insurance has really been a user of big data since its inception. Another example is fleet management.

Insurance 96

Insurance Risk Unstructured Data Data-driven 96

erwin

JUNE 27, 2019

Additional challenges, such as increasing regulatory pressures – from the General Data Protection Regulation (GDPR) to the Health Insurance Privacy and Portability Act (HIPPA) – and growing stores of unstructured data also underscore the increasing importance of a data modeling tool.

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

IBM Big Data Hub

SEPTEMBER 19, 2022

One way to achieve real-time analytics is with a combination of a time-series database (InfluxDB or TimescaleDB) or a NoSQL database (MongoDB) + a data warehouse + a BI tool: This architecture raises a question: Why would one use an operational database, and still need a data warehouse ? But wait, it gets better….

IoT 52

IoT Analytics Data Warehouse Manufacturing 52

IBM Big Data Hub

JUNE 21, 2023

Work began with watsonx.data , a data store that connects disparate data sources and allows developers to filter the data for things like profanity, hate speech or personally identifiable information. For AI Commentary, the team drew source material from nearly 130 million documents.

Consulting 70

Consulting Unstructured Data Digital Transformation Modeling 70

AWS Big Data

FEBRUARY 1, 2024

It includes massive amounts of unstructured data in multiple languages, starting from 2008 and reaching the petabyte level. In the training of GPT-3, the Common Crawl dataset accounts for 60% of its training data, as shown in the following diagram (source: Language Models are Few-Shot Learners ). It is continuously updated.

Metadata 98

Metadata Modeling Data Processing Unstructured Data 98

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Modeling Concept. Relational.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52