Confluent

APRIL 4, 2019

After cleansing data from all devices, the events can be dynamically routed to new Kafka topics, each of which represents a single device type. That device type may be extracted from a field in the original sensor data. final KStream<String, Event>[] cleansedEvents = events // …some data cleansing….

Kafka 108

Kafka Data Cleanse Retail Finance 108

Knowledge Hut

APRIL 19, 2023

Collecting your data: Collecting data from sources you identify, such as databases, spreadsheets, APIs, or websites. Clean Data: Clean data to remove duplicates, inconsistencies, and errors. This can be done manually or with a data cleansing tool. BigQuery is scalable and can handle large volumes of data.

Process 59

Process Data Mining Aggregated Data Portfolio 59

Knowledge Hut

SEPTEMBER 26, 2023

The basic power BI required skills are: How to connect to various data sources: Extracting data from various databases like SQL Server, MySQL, Oracle, etc. Kmowledge on loading data from Excel, CSV, JSON, and other file formats. Using web services and connecting to APIs and web data sources.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

ProjectPro

AUGUST 24, 2021

This project is an opportunity for data enthusiasts to engage in the information produced and used by the New York City government. You will set up MySQL for table creation and migrate data from RDBMS to Hive warehouse to arrive at the solution. Finally, this data is used to create KPIs and visualize them using Tableau.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2023

This process involves learning to understand the data and determining what needs to be done before the data becomes useful in a specific context. Discovery is a big task that may be performed with the help of data visualization tools that help consumers browse their data. What is the difference between SQL and MySQL?

Big Data 52

Big Data Hadoop Relational Database AWS 52

AltexSoft

AUGUST 29, 2023

These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Common structured data sources include SQL databases like MySQL, Oracle, and Microsoft SQL Server. Semi-structured data sources. Examples include HTML, XML, and JSON files.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52