Snowflake

MAY 9, 2024

It started when one capable model suited for text gained mainstream attention, and now, less than 18 months later, there is a long list of commercial and open-source gen AI models are now available, alongside new multimodal models that also understand images and other unstructured data.

Unstructured Data 121

Unstructured Data Manufacturing Retail Data Warehouse 121

Snowflake

JUNE 12, 2024

From unstructured data to boundless opportunities The potential applications for this technology are vast — from small financial firms to manufacturing conglomerates, from invoice reconciliation to evidence discovery. Take, for example, Northern Trust, the 134-year-old financial services company headquartered in Chicago.

Unstructured Data 112

Unstructured Data Finance Insurance Manufacturing 112

Striim

AUGUST 28, 2024

This integration allows AI to adapt instantly to new data, which is essential for applications where split-second decision-making is critical, including fraud detection, autonomous vehicles, and financial trading. It also powers real-time anomaly detection in cybersecurity and manufacturing, identifying threats and malfunctions as they occur.

Healthcare 52

Healthcare Retail Finance Algorithm 52

Cloudera

FEBRUARY 8, 2021

Micheal Ger, Managing Director Manufacturing & Automotive at Cloudera summed up it best with the insight, “Imparting intelligence into connected cars is complex – involving hardware, software, and deep domain expertise. connected manufacturing, and connected vehicles, see more of his perspective at [link]. challenges.

Manufacturing 110

Manufacturing Machine Learning Data Ingestion Electronics 110

Knowledge Hut

APRIL 26, 2024

Tons and tons of data are being generated each day and organizations have realized the vast potential that this data holds in terms of fueling innovation and predicting market trends and customer preferences. ML is used in these fields as a tool for predictions of sales forecasting, business growth, goods sold, manufacturing etc.

Datasets 98

Datasets Machine Learning Deep Learning Finance 98

Snowflake

JANUARY 18, 2024

Advanced analytics help manufacturers extract insights from their data and improve operations and decision-making. But for manufacturers, it’s often challenging to perform analytics with ERP data. A fragmented resource planning system causes data silos, making enterprise-wide visibility virtually impossible.

Manufacturing 111

Manufacturing Unstructured Data Cloud Architecture 111

Knowledge Hut

JULY 26, 2023

Users can use commands or user-friendly graphical interfaces to create, update, delete, and retrieve data from the database. They are used in a wide range of businesses and areas, including banking, healthcare, e-commerce, and manufacturing. Cloud-based databases provide flexibility, scalability, and cost-effectiveness.

Database 52

Database NoSQL Telecommunication MongoDB 52

Cloudera

OCTOBER 28, 2021

There is a wealth of data now available to make this possible. For example, the types of data sourced from other industries that we can use in the underwriting process include: Manufacturing – sensors (for quality, safety and maintenance-related). Another example is fleet management.

Insurance 99

Insurance Transportation Unstructured Data Manufacturing 99

Precisely

MARCH 27, 2023

Transforming Go-to-Market After years of acquiring and integrating smaller companies, a $37 billion multinational manufacturer of confectionery, pet food, and other food products was struggling with complex and largely disparate processes, systems, and data models that needed to be normalized.

Food 52

Food Consulting Pharmaceutical Data Lake 52

Knowledge Hut

APRIL 23, 2024

Below are some of the differences between Traditional Databases vs big data: Parameters Big Data Traditional Data Flexibility Big data is more flexible and can include both structured and unstructured data. Traditional Data is based on a static schema that can only work well with structured data.

Big Data 52

Big Data Relational Database Data Datasets 52

Cloudera

APRIL 20, 2021

Streaming Analytics can be used in many industries: Healthcare: Monitoring hospital patients to get the latest and most actionable data to inform patient interactions better. Manufacturing: Process millions of messages per minute from IoT devices and sensor data and use ML models to enhance the speed of production.

Hospitality 96

Hospitality Kafka Retail Data Ingestion 96

Cloudera

DECEMBER 3, 2020

A lot of the traditional in-person methods used for gathering data in insurance are now impossible and new ways of capturing data remotely are being implemented. The data being captured in forms of structured and unstructured data can unlock new insights.

Insurance 54

Insurance Unstructured Data Healthcare Manufacturing 54

Cloudera

DECEMBER 11, 2020

Without meeting GxP compliance, the Merck KGaA team could not run the enterprise data lake needed to store, curate, or process the data required to inform business decisions. It established a data governance framework within its enterprise data lake. Underpinning everything with security and governance.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Striim

AUGUST 22, 2024

For instance, say you work in a manufacturing plant and are looking to use real-time analytics to find faults in your machinery. You can use machine sensors to collect data and analyze it in real time to deduct if there are any signs of failure. You’ll also need to have an efficient way of collecting it.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Knowledge Hut

MARCH 26, 2024

Responsibilities: Define data architecture strategies and roadmaps to support business objectives and data initiatives. Design data models, schemas, and storage solutions for structured and unstructured data. Evaluate and recommend data management tools, database technologies, and analytics platforms.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 52

Knowledge Hut

NOVEMBER 18, 2023

Many companies manufacturing agricultural products use these techniques to learn about the soil type and plan their work strategies accordingly. AI Algorithms in Business Processes From advanced to basic AI algorithms, each can handle vast amounts of structured and unstructured data.

Algorithm 52

Algorithm IT Computer Science Unstructured Data 52

AltexSoft

AUGUST 29, 2023

Unstructured data sources. This category includes a diverse range of data types that do not have a predefined structure. Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JUNE 27, 2023

It helps to exchange data and interact with each other without human intervention. Applications: Healthcare, transportation, agriculture, and manufacturing. Big Data Overview: Big data refers to the massive volumes of structured and unstructured data generated by modern digital technologies.

Computer Science 52

Computer Science Entertainment Healthcare Finance 52

Knowledge Hut

JUNE 16, 2023

Data preparation: Because of flaws, redundancy, missing numbers, and other issues, data gathered from numerous sources is always in a raw format. After the data has been extracted, data analysts must transform the unstructured data into structured data by fixing data errors, removing unnecessary data, and identifying potential data.

Programming Language 52

Programming Language Data Science Cloud Computing Data Analytics 52

AltexSoft

MAY 12, 2022

Aiming at understanding sound data, it applies a range of technologies, including state-of-the-art deep learning algorithms. Audio analysis has already gained broad adoption in various industries, from entertainment to healthcare to manufacturing. Audio data file formats. Below we’ll give most popular use cases.

Machine Learning 122

Machine Learning Building Deep Learning Datasets 122

Knowledge Hut

MAY 2, 2024

Spark is being used in more than 1000 organizations who have built huge clusters for batch processing, stream processing, building warehouses, building data analytics engine and also predictive analytics platforms using many of the above features of Spark. Let’s look at some of the use cases in a few of these organizations.

Scala 52

Scala Hospitality Healthcare Retail 52

Knowledge Hut

MAY 31, 2023

It can also be used to generate reports and forecasts based on inventory data. This type of project can be useful for businesses in various industries, such as retail, manufacturing and distribution. Systems can be designed to monitor inventory levels, suppliers and purchases.

Database 52

Database Coding MongoDB Project 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

DECEMBER 26, 2023

Data science is a subject of study that utilizes scientific methods, processes, algorithms, and systems to uproot knowledge and insights from data in various forms, both structured and unstructured. Data science is related to data mining and big data.

Data Science 52

Data Science Consulting Computer Science Education 52

Knowledge Hut

JUNE 26, 2023

Multiple types of data exist within organizations, and it is the obligation of data architects to standardize them so that data analysts and scientists can use them interchangeably. If data scientists and analysts are pilots, data engineers are aircraft manufacturers.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Snowflake

FEBRUARY 6, 2024

An end-user-facing data catalog or marketplace can improve discoverability and access. Transform unstructured data to expand available internal data. To ensure that all data is made available, organizations must adopt tools to transform unstructured data into usable formats.

Unstructured Data 128

Unstructured Data Retail Data Manufacturing 128

ProjectPro

JANUARY 28, 2022

This is especially useful in unstructured data like images where anomalies could be any type of image other than the one trained on the model. To summarise, unsupervised anomaly detection methods work best when you’re not aware of the type of anomalies that may occur, especially with unstructured data.

Machine Learning 52

Machine Learning Python Datasets Algorithm 52

ProjectPro

JUNE 1, 2017

Zensar Technologies announced the launch of its new big data platform for effortless end to end information management to address complex business problems through empowered data driven insights.The new big data platform provides data driven decision making culture by integrating the existing assets of an organization with various unstructured data (..)

Hadoop 52

Hadoop Medical Pipeline-centric Database-centric 52

Knowledge Hut

DECEMBER 27, 2023

Supply Chain Executive Supply Chain Executives are responsible for how companies drive the smooth flow of goods from manufacturing to delivery. In recent years, the demand for Data Scientists has grown on a huge scale. A Data Scientist is a computer expert with skills like collecting and analyzing data.

Banking 52

Banking Finance Recruitment Portfolio 52

ProjectPro

NOVEMBER 14, 2015

As we step into the latter half of the present decade, we can’t help but notice the way Big Data has entered all crucial technology-powered domains such as banking and financial services, telecom, manufacturing, information technology, operations, and logistics.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Knowledge Hut

DECEMBER 26, 2023

Importance of Big Data Companies Big Data is intricate and can be challenging to access and manage because data often arrives quickly in ever-increasing amounts. Both structured and unstructured data may be present in this data. Microsoft's Big Data strategy is broad and expanding rapidly.

Big Data 52

Big Data Unstructured Data Amazon Web Services Hadoop 52

ProjectPro

SEPTEMBER 26, 2014

BI professionals use various tools to draw useful data that are used to generate customized reports and this is where the Hadoop File Distribution System (HDFS) proves itself. Today, the manufacturing sector uses Hadoop for assessment of product quality. Hadoop has proven its usefulness in various segments of business.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

Knowledge Hut

APRIL 23, 2024

Targeted Marketing & Campaigns: Big data gives telecom companies the ability to divide up their client base, analyze the use patterns and demographic information, and create personalized marketing campaigns and offers that will boost customer acquisition and retention.

Big Data 52

Big Data Retail Recruitment Transportation 52

Monte Carlo

JANUARY 16, 2024

Data lake and data warehouse convergence The data lake vs data warehouse question is constantly evolving. The maxim that data warehouses hold structured data while data lakes hold unstructured data is quickly breaking down.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Snowflake

APRIL 10, 2023

The platform pushes the boundaries of natural language processing (NLP) with a diverse, rapidly expanding (and almost limitless) number of use cases that extends from automotive manufacturing and chemicals to HR, insurance, legal, finance, and government. From there, we can process information not unlike how humans do.

Unstructured Data 59

Unstructured Data Manufacturing Insurance Government 59