Cloudera

DECEMBER 17, 2020

When it comes to machine learning (ML) in the enterprise, there are many misconceptions about what it actually takes to effectively employ machine learning models and scale AI use cases. Accelerating the Full Machine Learning Lifecycle With Cloudera Data Platform.

Machine Learning 82

Machine Learning Data Science Data Pipeline Raw Data 82

AltexSoft

AUGUST 25, 2021

Natural language processing or NLP is a branch of Artificial Intelligence that gives machines the ability to understand natural human speech. NLP techniques open tons of opportunities for human-machine interactions that we’ve been exploring for decades. Machine learning-based NLP — the basic way of doing NLP.

Process 139

Process Deep Learning Datasets Machine Learning 139

Edureka

JULY 5, 2024

Tableau Prep is a fast and efficient data preparation and integration solution (Extract, Transform, Load process) for preparing data for analysis in other Tableau applications, such as Tableau Desktop. simultaneously making raw data efficient to form insights.

Data Preparation 40

Data Preparation Process BI ETL Tools 40

Zalando Engineering

MARCH 21, 2017

At Zalando adtech lab in Hamburg, machine learning drives many of our production systems to build great user experiences. Instead, we can focus on building a flexible and versatile model that can be easily extended to new types of input data and applied to a variety of prediction tasks.

Deep Learning 52

Deep Learning Raw Data Machine Learning AWS 52

ProjectPro

FEBRUARY 8, 2023

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses.

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

SEPTEMBER 26, 2023

Workspace is the platform where power BI developers create reports, dashboards, data sets, etc. Dataset is the collection of raw data imported from various data sources for the purpose of analysis. DirectQuery and Live Connection: Connecting to data without importing it, ideal for real-time or large datasets.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

DataKitchen

JULY 27, 2023

You can use it for big data analytics and machine learning workloads. Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. It provides data prep, management, and enterprise data warehousing tools.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

DataKitchen

DECEMBER 9, 2022

DataOps involves collaboration between data engineers, data scientists, and IT operations teams to create a more efficient and effective data pipeline, from the collection of raw data to the delivery of insights and results. Overall, DataOps is an essential component of modern data-driven organizations.

Machine Learning 52

Machine Learning Data Preparation Government Data Analytics 52

Knowledge Hut

OCTOBER 4, 2023

While the numbers are impressive (and a little intimidating), what would we do with the raw data without context? The tool will sort and aggregate these raw data and transport them into actionable, intelligent insights. If this trend continues to evolve, it will nearly double by 2025.

BI 52

BI Systems Raw Data Data Preparation 52

Knowledge Hut

NOVEMBER 27, 2023

Developing technical skills is essential, starting with foundational knowledge in mathematics, including calculus and linear algebra, which underpin machine learning and deep learning concepts. Through the article, we will learn what data scientists do, and how to transits to a data science career path.

Data Science 52

Data Science Datasets Machine Learning Portfolio 52

Knowledge Hut

JANUARY 25, 2024

Data cleaning is like ensuring that the ingredients in a recipe are fresh and accurate; otherwise, the final dish won't turn out as expected. It's a foundational step in data preparation, setting the stage for meaningful and reliable insights and decision-making. Here's why cleaning data is super important: 1.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

Ascend.io

AUGUST 16, 2023

The collection and preparation of data used for analytics are achieved by building data pipelines that ingest raw data and transform it into useful formats leveraging cloud data platforms like Snowflake, Databricks, and Google BigQuery.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Ascend.io

JANUARY 2, 2024

The key differentiation lies in the transformational steps that a data pipeline includes to make data business-ready. Ultimately, the core function of a pipeline is to take raw data and turn it into valuable, accessible insights that drive business growth. analytics, machine learning)? cleaning, formatting)?

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Knowledge Hut

JUNE 28, 2023

Structured data from databases, data warehouses, and operational systems. Goal Extracting valuable information from raw data for predictive or descriptive purposes. Methods and Techniques Machine learning, statistical analysis, clustering, classification, association rule mining, etc.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. There are several types of data testing tools.

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

Knowledge Hut

JUNE 16, 2023

Analyzing data with statistical and computational methods to conclude any information is known as data analytics. Finding patterns, trends, and insights, entails cleaning and translating raw data into a format that can be easily analyzed. They then arrange the data in a suitable format that is simple to understand.

Programming Language 52

Programming Language Data Analytics Data Science Cloud Computing 52

Edureka

JANUARY 23, 2023

The use of data by companies to understand business patterns and predict future occurrences has been on the rise. With the availability of new technologies like machine learning, it has become easy for experts to analyse vast quantities of information to find patterns that will help establishments make better decisions.

Data Mining 52

Data Mining Banking Retail Medical 52

AltexSoft

MARCH 18, 2022

Machine learning is no exception. You’ve probably heard of two main ML techniques — supervised and unsupervised learning. The mixture of two gave birth to the happy medium known as semi-supervised learning. Supervised vs unsupervised vs semi-supervised machine learning in a nutshell.

Datasets 52

Datasets Machine Learning Algorithm Raw Data 52

Knowledge Hut

JANUARY 30, 2024

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

Databand.ai

AUGUST 30, 2023

Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing, and maintaining data quality. There are several types of data testing tools.

Data Cleanse 52

Data Cleanse Data Validation Data Pipeline Datasets 52

U-Next

SEPTEMBER 28, 2022

Let’s learn the types of HR Analytics one by one: . Descriptive HR Analytics meaning describes or summarizes raw data to make it human-interpretable. Data preparation occurs before the analysis stage and is crucial to ensuring correctness; it is also one of the most time-consuming tasks for the analyst. .

Recruitment 52

Recruitment Algorithm Machine Learning Utilities 52

AltexSoft

MAY 14, 2021

Modern technologies allow gathering both structured (data that comes in tabular formats mostly) and unstructured data (all sorts of data formats) from an array of sources including websites, mobile applications, databases, flat files, customer relationship management systems (CRMs), IoT sensors, and so on. The Ginger.io

Big Data 78

Big Data Data Analytics IT NoSQL 78

Rockset

MARCH 19, 2019

“With Rockset, I don’t have to worry about data being typed or formatted in a way I didn’t anticipate, and I don’t have to modify my code every time the schema changes. Rockset just sucks in all the raw data and makes it accessible using SQL, so it's faster and easier to develop on the data.”

SQL 40

SQL Raw Data Manufacturing Relational Database 40

U-Next

SEPTEMBER 9, 2022

Making judgments and predictions via Machine Learning, prescriptive analytics, and predictive causal analysis is the major application of Data Science. What is Data Science? . They gather, purge, and arrange data that can eventually be leveraged to make business growth strategies. . Machine Learning .

Data Science 40

Data Science Computer Science Machine Learning Hadoop 40

Knowledge Hut

OCTOBER 27, 2023

Microsoft created Power BI, a business analytics tool that enables users to visualize and analyze data from various sources quickly and interactively. It provides a wide range of features and functionalities, including data preparation, data modeling, data visualization, and collaboration tools.

BI 52

BI Project Datasets Healthcare 52

ProjectPro

JANUARY 31, 2022

Snowflake Features that Make Data Science Easier Here are three Snowflake attributes that make running successful data science projects easier for businesses- 1. Centralized Source of Data When training machine learning models, data scientists must consider a wide range of data.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

APRIL 27, 2016

Pig Hadoop dominates the big data infrastructure at Yahoo as 60% of the processing happens through Apache Pig Scripts. Today, Hive is used at Facebook to store more than 2 petabytes of uncompressed data and regularly loads more than 15 terabytes of data daily.

Hadoop 40

Hadoop Big Data Technology Kafka 40

Knowledge Hut

OCTOBER 30, 2023

The role of a Power BI developer is extremely imperative as a data professional who uses raw data and transforms it into invaluable business insights and reports using Microsoft’s Power BI. The capacity to translate business requirements into data visualization solutions. Who is a Power BI Developer?

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. Machine Learning web service to host forecasting code.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

DECEMBER 26, 2023

Learn all about Business Intelligence and Visualization training and earn business intelligence certifications. Business intelligence (BI) is the collective name for a set of processes, systems, and technologies that turn raw data into knowledge that can be used to operate enterprises profitably. Enroll now!

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

ProjectPro

MAY 20, 2015

It provides the first purpose-built Adaptive Data Preparation Solution(launched in 2013) for data scientist, IT teams, data curators, developers, and business analysts -to integrate, cleanse and enrich raw data into meaningful analytic ready big data that can power operational, predictive , ad-hoc and packaged analytics.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

ProjectPro

DECEMBER 22, 2016

If you are aspiring to be a data analyst then the core competencies that you should be familiar with are distributed computing frameworks like Hadoop and Spark, knowledge of programming languages like Python, R , SAS, data munging, data visualization, math , statistics , and machine learning.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

U-Next

SEPTEMBER 23, 2022

In Big Data systems, data can be left in its raw form and subsequently filtered and structured as needed for specific analytical needs. In other circumstances, it is preprocessed using data mining methods and data preparation software to prepare it for ordinary applications. . Ingestion .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineer performs a multi-faceted role in an organization by identifying, extracting, and delivering the data sets in useful formats. A Big Data Engineer also constructs, tests, and maintains the Big Data architecture. Your organization will use internal and external sources to port the data.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. There are open data platforms in several regions (like data.gov in the U.S.).

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

JUNE 24, 2021

Microsoft Excel: A successful Excel spreadsheet helps to organize raw data into a more readable format. With more complex data, Excel allows customization of fields and functions that can make calculations based on the data in the excel spreadsheet. Topic modelling can also be used to classify large datasets of emails.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40