ProjectPro

FEBRUARY 16, 2023

The study and pattern of how humans think is the foundation of artificial intelligence, and the algorithm replicates human brain functions. Focus Historical data analysis, reporting, and visualization. Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

DataKitchen

FEBRUARY 27, 2024

LLMs have the potential to revolutionize how we interact with data, automate processes, and extract insights. However, the foundation of their success rests not just on sophisticated algorithms or computational power but on the quality and integrity of the data they are trained on and interact with.

Data Engineering 48

Data Engineering Data Engineer Engineering Unstructured Data 48

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

AltexSoft

OCTOBER 25, 2021

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. This allows machines to extract value even from unstructured data. Healthcare organizations generate a lot of text data. Source: Linguamatics.

Medical 52

Medical Healthcare Process Hospitality 52

Knowledge Hut

JANUARY 19, 2024

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. Data Manipulation Techniques to organize and present data meaningfully.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Data Visualization Graphic representation of a set or sets of data. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

ProjectPro

MARCH 17, 2021

Machine learning makes use of a set of learning algorithms (supervised or unsupervised learning process) to analyze the data, interpret it, learn from it, and make the best possible business decisions based on the learnings. But how will the ML algorithm know which one is Apple and which one is Orange?

Deep Learning 52

Deep Learning Machine Learning Algorithm Datasets 52

Knowledge Hut

JULY 26, 2023

Variety: Variety represents the diverse range of data types and formats encountered in Big Data. Traditional data sources typically involve structured data, such as databases and spreadsheets. Handling this variety of data requires flexible data storage and processing methods.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. You can use open-source medical datasets like CHDS (Child Health and Development Studies), HCUP, Medicare to test your machine learning algorithm. Text Processing b. Text Sequencing c.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

Zalando Engineering

NOVEMBER 6, 2017

To understand fashion in machine learning, some of the technical challenges taken on by the FCP team were: Data models - built on structured data sets. Quality structured data is not easy to get in fashion. Unstructured data - online fashion data is stored in HTML blogs and social media posts.

Data Science 40

Data Science Deep Learning Media Unstructured Data 40

ProjectPro

SEPTEMBER 14, 2016

Concisely, a hadoop developer plays with the data, transforms it, decodes it and ensure that it is not destroyed. Most of the hadoop developers receive unstructured data through flume or structured data through RDBMS and perform data cleaning using various tools in the hadoop ecosystem.

Hadoop 40

Hadoop Unstructured Data Java Big Data 40

ProjectPro

NOVEMBER 14, 2015

Hadoop can be used to carry out data processing using either the traditional (map/reduce) or Spark-based (providing an interactive platform to process queries in real-time) approach. Given a graphical relation between variables, an algorithm needs to be developed which predicts which two nodes are most likely to be connected?

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

SEPTEMBER 1, 2015

Once big data is loaded into Hadoop, what is the best way to use this data? Collecting huge amounts of unstructured data does not help unless there is an effective way to draw meaningful insights from it. Hadoop Developers have to filter and aggregate the data to leverage it for business analytics.

Hadoop 40

Hadoop Java Unstructured Data SQL 40

ProjectPro

AUGUST 6, 2015

Companies like Electronic Arts, Riot Games are using big data for keeping a track of game play which helps predict performance of the play by analysing 4TB of operational logs and 500GB of structured data. Sports brands like ESPN have also got on to the big data bandwagon.

Big Data 52

Big Data Hadoop Insurance Media 52

Edureka

JANUARY 18, 2024

For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? Data science is the study of data to extract knowledge and insights from structured and unstructured data using scientific methods, processes, and algorithms.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

Knowledge Hut

DECEMBER 26, 2023

This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc. This is one of the major reasons behind the popularity of data science.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

MAY 20, 2015

Several big data companies are looking to tame the zettabyte’s of BIG big data with analytics solutions that will help their customers turn it all in meaningful insights. Palantir Metropolis- This product focusses on information management, data integration and quantitative analytics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

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.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

APRIL 25, 2024

Variety: Unstructured data, semi-structured data, and raw data are only a few examples of the variety of data kinds that exist. It is effective to use a recommendation engine that makes use of data filtering technologies that gather data and then filter it using algorithms.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Knowledge Hut

MARCH 27, 2024

Big data tools are used to perform predictive modeling, statistical algorithms and even what-if analyses. Some important big data processing platforms are: Microsoft Azure. Why Is Big Data Analytics Important? Data can be processed for the application of big data analysis over the cloud and segregated using Xplenty.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

NOVEMBER 17, 2023

After the introduction of cloud computing, the need for managing expanding data is getting more critical. But running complex algorithms on personal machines is getting challenging due to memory and computing constraints. People started leveraging the cloud's power to run complex algorithms to solve these challenges.

AWS 52

AWS Data Science Certification Amazon Web Services 52

AltexSoft

JULY 27, 2021

By utilizing ML algorithms and data, it is possible to create smart models that can precisely predict customer intent and as such provide quality one-to-one recommendations. At the same time, the continuous growth of available data has led to information overload — when there are too many choices, complicating decision-making.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

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

AltexSoft

NOVEMBER 1, 2023

NER for structuring unstructured data NER plays a pivotal role in converting unstructured text into structured data. Modern content platforms, from news websites to streaming services like Netflix, harness NER to fine-tune their recommendation algorithms.

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

Snowflake

MARCH 30, 2023

Schema drift on a wide table structure needs an ALTER TABLE statement, whereas the tall table structure does not. By adding the ability to run your Java , Scala , and Python within the platform, you no longer need to rely on external programming interfaces to run your transformations/algorithms. Enter Snowpark !

Engineering 79

Engineering Raw Data Data Science Scala 79

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

OCTOBER 20, 2021

The estimator automatically performs the algorithm selection as well as the hyperparameter tuning Auto-Keras : To recall, Keras is an open-source library that provides a Python interface into the world of Artificial Intelligence, especially Tensorflow. Auto-Weka : Weka is a top-rated java-based machine learning software for data exploration.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

JUNE 7, 2021

Main users of Hive are data analysts who work with structured data stored in the HDFS or HBase. Data management and monitoring options. Among solutions facilitation data management are. Hadoop uses Apache Mahout to run machine learning algorithms for clustering, classification, and other tasks on top of MapReduce.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

OCTOBER 30, 2018

The abundant growth of data, maturation of machine algorithms, and future regulatory compliance demands from the European Union’s General Data Protection Regulation (GDPR) will shift the landscape for creating a single source of the truth for customer data. Additionally, they only provide one piece of the puzzle.

Unstructured Data 42

Unstructured Data Data Lake Algorithm Machine Learning 42

AltexSoft

AUGUST 22, 2022

The self-service functionally allows the entire organization to find relevant data faster and gain valuable insights. Support for different data types and use cases. A data fabric supports structured, unstructured, and semi-structured data whether it comes in real-time or generated in batches.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Cloudera

SEPTEMBER 6, 2018

Handle increases in data volume gracefully. Support machine learning (ML) algorithms and data science activities, to help with name matching, risk scoring, link analysis, anomaly detection, and transaction monitoring. Provide audit and data lineage information to facilitate regulatory reviews. Cloudera Enterprise.

Banking 40

Banking Machine Learning Big Data Scala 40

U-Next

AUGUST 11, 2022

A Data Scientist’s job entails deciphering and analyzing complex, unstructured data gathered from several sources. Read on to learn about the career opportunities and salary of a Data Scientist. Who are Data Scientists, and what is their work? Skill requirements for Data Science. Introduction.

Data Science 40

Data Science Data Cleanse Unstructured Data Machine Learning 40