Knowledge Hut

APRIL 25, 2024

Big data vs machine learning is indispensable, and it is crucial to effectively discern their dissimilarities to harness their potential. Big Data vs Machine Learning Big data and machine learning serve distinct purposes in the realm of data analysis. It focuses on collecting, storing, and processing extensive datasets.

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

Data Engineering Weekly

MAY 8, 2023

The finance department has requested your assistance with their annual balance sheet, explicitly matching all entries from the company's bank account with receipts submitted by employees for their professional expenses. Unfortunately, this approach results in unstructured data that is difficult to work with.

Process 52

Process Banking Raw Data Finance 52

RandomTrees

JUNE 17, 2024

AI technology is revolutionizing and changing the way that fraud detection and prevention are being practiced, especially in the finance industry. This should not be taken lightly by any finance institution because it would result in biased treatment of some groups within their jurisdiction.

Banking 52

Banking Deep Learning Machine Learning Finance 52

Snowflake

APRIL 8, 2024

Capable of a headless deployment into Snowpark Container Services, BigGeo can be used to speed up queries of data stored in Snowflake, gather those insights into a dashboard, visualize them on a map, and more. It deploys gen AI components as containers on Snowpark Container Services, close to the customer’s data.

Pipeline-centric 128

Pipeline-centric Food Healthcare Unstructured Data 128

Edureka

SEPTEMBER 23, 2024

What is Data Science? Data Science is an applied science that deals with the process of obtaining valuable information from structured and unstructured data. They use various tools, techniques, and methodologies borrowed from statistics, mathematics computer science to analyze large amounts of data.

Data Science 40

Data Science Data Mining Computer Science Finance 40

Cloudera

DECEMBER 11, 2020

These include the use of more data sources to gain insights and how cloud technologies can assist with digital transformation goals to be more agile and achieve objectives more quickly. Data Variety. Insurance and finance are two industries that rely on measuring risk with historical data models.

Insurance 94

Insurance Unstructured Data Finance Machine Learning 94

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. It has found applications in all facets of our lives from healthcare to automobiles to banking and finance.

Machine Learning 98

Machine Learning Datasets Deep Learning Finance 98

Edureka

JUNE 7, 2024

paintings, songs, code) Historical data relevant to the prediction task (e.g., Deep Learning Models Deep learning models are particularly adept at extracting insights from unstructured data like images, text, and audio. Getting the picture?

Deep Learning 114

Deep Learning Media Manufacturing Algorithm 114

phData: Data Engineering

NOVEMBER 8, 2024

It enables analysts and data engineers to “go back in time” and investigate how data looked at specific points, a critical feature for industries with stringent audit requirements, such as finance, healthcare, and e-commerce. They also support ACID transactions, ensuring data integrity and stored data reliability.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Knowledge Hut

APRIL 23, 2024

They also facilitate historical analysis, as they store long-term data records that can be used for trend analysis, forecasting, and decision-making. Big Data In contrast, big data encompasses the vast amounts of both structured and unstructured data that organizations generate on a daily basis.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

JANUARY 18, 2024

Data Science is a field of study that handles large volumes of data using technological and modern techniques. This field uses several scientific procedures to understand structured, semi-structured, and unstructured data. Both data science and software engineering rely largely on programming skills.

Software Engineering 97

Software Engineering Software Engineer Data Science Engineering 97

Knowledge Hut

JANUARY 18, 2024

People are always looking to make their lives exciting, and therefore they take the support of the internet; this means that Big Data is continuously growing. If the decisions taken in an organization are data-driven, then a company can make smarter decisions. They also have platforms where data scientists can share their knowledge.

Data Science 98

Data Science Amazon Web Services Big Data Finance 98

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

Knowledge Hut

JUNE 27, 2023

Computer science is driving innovation in a variety of other industries, including healthcare, finance, & transport. In finance, computer science is facilitating faster, more secure, accurate transactions through blockchain and distributed ledger technologies. Applications: Finance, healthcare, supply chain, as well as voting.

Computer Science 52

Computer Science Entertainment Healthcare Finance 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

Striim

AUGUST 28, 2024

Real-time data integration allows models to process the most recent data points, reducing lag between data generation and actionable insights. This is crucial in fields like finance, where market conditions shift rapidly, or e-commerce, where user behavior and inventory status constantly change.

Healthcare 52

Healthcare Retail Algorithm Finance 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

Knowledge Hut

JULY 28, 2023

Data Types and Dimensionality ML algorithms work well with structured and tabular data, where the number of features is relatively small. DL models excel at handling unstructured data such as images, audio, and text, where the data has a large number of features or high dimensionality. When to Use Deep Learning 1.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

Knowledge Hut

JANUARY 18, 2024

Roles and Responsibilities Finding data sources and automating the data collection process Discovering patterns and trends by analyzing information Performing data pre-processing on both structured and unstructured data Creating predictive models and machine-learning algorithms Average Salary: USD 81,361 (1-3 years) / INR 10,00,000 per annum 3.

Data Science 98

Data Science Business Analyst Data Architect ETL Method 98

Towards Data Science

DECEMBER 4, 2023

We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g.

Data Engineer 82

Data Engineer Data Engineering Engineering Data Lake 82

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is a NoSQL database that’s been making rounds in the data science community. MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. Let us see where MongoDB for Data Science can help you.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Cloudera

OCTOBER 28, 2021

In the last few years, Commercial Insurers have been making great strides in expanding the use of their data. The approach is very evolutionary; the initial focus tends to be aimed at cost savings and starts with structured data. This results in enhancements in finance reporting or compliance.

Insurance 97

Insurance Transportation Unstructured Data Manufacturing 97

Cloudera

JANUARY 28, 2022

The question of the data to use will include the basics of transactional and enterprise data sources, but should expand to broader questions that will further shape the deployment strategy including third-party data, the need for real-time and/or unstructured data, ML and AI tools, etc.

Cloud 114

Cloud Banking Data Governance Government 114

Cloudera

APRIL 20, 2021

Finance/Banks : Modernize bank’s customer application by incorporating streaming capabilities to millions of customer interactions without failure and better customer experience. Companies tried processing these data through batch processing but saw workloads run much slower from hours to days.

Kafka 95

Kafka Hospitality Retail Data Ingestion 95

ProjectPro

JANUARY 27, 2023

Real-World ETL Use Cases and Applications Across Industries This blog discusses the numerous ETL use cases in various industries, including finance, healthcare, and retail. Standard technology does a good job of handling structured data, numerical data, and transactions, but it struggles to retrieve and analyze textual data.

BI 52

BI ETL Tools Retail Healthcare 52

Cloudera

DECEMBER 3, 2020

The data being captured in forms of structured and unstructured data can unlock new insights. Leveraging CDP, the cloud can store the structured and unstructured data, and allow new types of data, processes, and models based on real-time analytics to be spun up and scaled faster than ever before.

Insurance 53

Insurance Unstructured Data Healthcare Manufacturing 53

Knowledge Hut

DECEMBER 27, 2023

It enhances the students' abilities in Administration, Banking, Finance, Marketing , or Sales. The MBA course allows you to upskill your leadership roles in various sectors, including Banking, Finances, Sales, and many more. Masters in Finance Management Suppose you are struggling after BBA; which course is best?

Banking 52

Banking Recruitment Finance Portfolio 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Unstructured data represents up to 80-90 percent of the entire datasphere.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

APRIL 23, 2024

Big Data certification course will support you in learning big data skills from the greatest mentors to help you build a career in big data. Top 10 Disadvantages of Big Data 1. Need for Skilled Personnel We see data in different forms; it can be categorized into structured, semi-structured, and unstructured data.

Big Data 52

Big Data Media Government Big Data Skills 52

U-Next

AUGUST 18, 2022

These factors all work together to help us uncover underlying patterns or observations in raw data that can be extremely useful when making important business choices. Both organized and unstructured data are used in Data Science. Data Science is thus entirely concerned with the present moment.

Unstructured Data 40

Unstructured Data Data Science Medical Business Intelligence 40

Knowledge Hut

MAY 9, 2024

Top recruiters include Amazon, Google, Microsoft, and industries like finance, healthcare, and e-commerce. According to Glassdoor, the average annual salary for a data scientist in the United States is over USD 110,000, with top earners making well over USD 150,000.

Data Science 52

Data Science Data Architect Data Mining Programming Language 52

Knowledge Hut

MAY 31, 2023

The development process may include tasks such as building and training machine learning models, data collection and cleaning, and testing and optimizing the final product. Impact: AI can positively impact society, from healthcare and education to finance and transportation.

Project 96

Project Healthcare Deep Learning Transportation 96

Cloudera

SEPTEMBER 15, 2022

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API.

Systems 87

Systems Hadoop Metadata Telecommunication 87

Knowledge Hut

NOVEMBER 28, 2023

Computer science, mathematics, and statistics training are often required for data science positions. Data scientists do more than just model and process structured and unstructured data; they also translate the results into useful strategies for stakeholders.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

Knowledge Hut

JULY 26, 2023

They frequently include features like down sampling, data preservation regulations, and time-based functionalities. These databases are widely utilized in a variety of industries, including finance, energy, telecommunications, and monitoring systems. Cloud-based databases provide flexibility, scalability, and cost-effectiveness.

Database 52

Database NoSQL Telecommunication MongoDB 52

Knowledge Hut

JUNE 20, 2023

Search-Based Discovery Tools Search-based discovery tools allow users to utilize search terms in order to create and improve views and perform analysis of both structured and unstructured data. Business analysts perform the process of making a portfolio of potential candidates who may prove to be an asset to the company.

Business Analyst 52

Business Analyst Banking Cloud Computing Unstructured Data 52

Edureka

AUGUST 2, 2023

Data processing analysts are experts in data who have a special combination of technical abilities and subject-matter expertise. They are essential to the data lifecycle because they take unstructured data and turn it into something that can be used.

Data Process 52

Data Process Process Data Cleanse Data Mining 52