Knowledge Hut

JANUARY 25, 2024

Encoding categorical variables, scaling numerical features, creating new features, aggregating data. One-hot encoding categorical variables, standardizing numerical features, aggregating data. Best Data cleaning tools and software Data cleaning is a crucial step in data preparation, ensuring data accuracy and reliability.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

DareData

JULY 5, 2023

We've seen this happen in dozens of our customers: data lakes serve as catalysts that empower analytical capabilities. If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. And what is the reason for that?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

AltexSoft

DECEMBER 23, 2022

This is because the target system can perform data transformation and loading in parallel, which speeds up the process. A project requires large amounts of both structured and unstructured data , such as data generated by sensors, GPS trackers, and video recorders. Aggregation.

Process 52

Process Building Raw Data Data Lake 52

ProjectPro

FEBRUARY 8, 2023

Create The Connector for Source Database The first step is having the source database, which can be any S3, Aurora, and RDS that can hold structured and unstructured data. Glue works absolutely fine with structured as well as unstructured data.

AWS 98

AWS Scala Metadata Data Lake 98

Striim

AUGUST 22, 2024

To achieve this, combine data from the sum of your sources. For this purpose, you can use ETL (extract, transform, and load) tools or build a custom data pipeline of your own and send the aggregated data to a target system, such as a data warehouse.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Netflix Tech

APRIL 26, 2022

The Iceberg table created by Keystone contains large blobs of unstructured data. These large unstructured blogs are not efficient for querying, so we need to transform and store this data in a different format to allow efficient queries. Was data corrupted at rest? Compute applications follow daily trends.

Metadata 77

Metadata Datasets Machine Learning Designing 77

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 2- Internal Data transformation at LakeHouse.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

AUGUST 4, 2021

They typically contain structured data and take less time for setup — normally 3 to 6 months for on-premise solutions. A data lake is a central repository used to store massive amounts of both structured and unstructured data coming from a great variety of sources.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

OCTOBER 28, 2015

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 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

AltexSoft

SEPTEMBER 21, 2023

These indices are specially designed data structures that map out the data for rapid searches, allowing for the retrieval of queries in milliseconds. As a result, Elasticsearch is exceptionally efficient in managing structured and unstructured data.

Engineering 52

Engineering NoSQL Programming Language Java 52

Knowledge Hut

SEPTEMBER 6, 2023

This is an entry-level database certification, and it is a stepping stone for other role-based data-focused certifications, like Azure Data Engineer Associate, Azure Database Administrator Associate, Azure Developer Associate, or Power BI Data Analyst Associate. Skills acquired : Core data concepts. Data storage options.

Database 52

Database Certification MongoDB MySQL 52

phData: Data Engineering

JANUARY 3, 2022

This likely requires you to aggregate data from your ERP system, your supply chain system, potentially third-party vendors, and data around your internal business structure. This is where data science comes into the picture. What is Data Modeling?

Data Engineer 52

Data Engineer Data Engineering Engineering Data Governance 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52