Cloudera

DECEMBER 17, 2020

While it’s important to have the in-house data science expertise and the ML experts on-hand to build and test models, the reality is that the actual data science work — and the machine learning models themselves — are only one part of the broader enterprise machine learning puzzle.

Machine Learning 83

Machine Learning Data Science Data Pipeline Raw Data 83

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

Knowledge Hut

JUNE 28, 2023

In our data-driven world, our lives are governed by big data. The TV shows we watch, the social media we follow, the news we read, and even the optimized routes we take to work are all influenced by the power of big data analytics. Structured data from databases, data warehouses, and operational systems.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

Knowledge Hut

MAY 1, 2024

From tracking the websites we visit - how long, how often - to what we purchase and where we go - our digital footprint is an immense source of data for a lot of businesses. Between our laptops, smartphones and our tablets - almost everything we do translates into some form of data. It sounds like a mighty hefty job, doesn’t it?

Data Science 94

Data Science Raw Data Manufacturing Retail 94

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

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 97

Engineering Raw Data Data Science Scala 97

Knowledge Hut

APRIL 25, 2024

These technologies are necessary for data scientists to speed up and increase the efficiency of the process. The main features of big data analytics are: 1. Data wrangling and Preparation The idea of Data Preparation procedures conducted once during the project and performed before using any iterative model.

Big Data 52

Big Data Data Analytics Manufacturing Retail 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 Unstructured Data 40

U-Next

SEPTEMBER 7, 2022

Autonomous data warehouse from Oracle. . What is Data Lake? . Essentially, a data lake is a repository of raw data from disparate sources. A data lake stores current and historical data similar to a data warehouse. Synapse on Microsoft Azure. . The Snowflake database. .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Rockset

DECEMBER 9, 2019

This obviously introduces a number of problems for businesses who want to make sense of this data because it’s now arriving in a variety of formats and speeds. To solve this, businesses employ data lakes with staging areas for all new data. This is where technologies like Rockset can help.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

Knowledge Hut

DECEMBER 26, 2023

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. Business intelligence solutions comBIne technology and strategy for gathering, analyzing, and interpreting data from internal and external sources.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

U-Next

SEPTEMBER 28, 2022

Descriptive HR Analytics meaning describes or summarizes raw data to make it human-interpretable. KPI (key performance indicator) governance is critical to the success of descriptive analytics. . Data is gathered from sources such as reports and databases. Let’s learn the types of HR Analytics one by one: .

Recruitment 52

Recruitment Algorithm Utilities Machine Learning 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. There are three stages in this real-world data engineering project.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2022

Feature engineering is a computational technique that entails changing raw data into more relevant features resulting in accurate predictive models. Traditional data preparation platforms, including Apache Spark, are unnecessarily complex and inefficient, resulting in fragile and costly data pipelines.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

JUNE 24, 2021

Data Cleaning: To improve the data quality and filter the noisy, inaccurate, and irrelevant data for analysis, data cleaning is a key skill needed for all analytics job roles. Microsoft Excel: A successful Excel spreadsheet helps to organize raw data into a more readable format. to analyze the data.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

U-Next

SEPTEMBER 23, 2022

Financial services firms use big data platforms for risk management and real-time market data analysis. . Big data is used by manufacturers and transportation businesses to manage supply chains and optimize delivery routes. . Understanding The Ecosystem of Big Data . Components of Database of the Big Data Ecosystem .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

RandomTrees

FEBRUARY 6, 2024

Investigating the contribution of Gen AI to data integration and management Smart data integration : It automatically identifies data relationships, maps schemas, and harmonizes data formats, enabling organizations to establish a unified data view.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation.

Big Data 52

Big Data Coding Project Hadoop 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64