Knowledge Hut

APRIL 19, 2023

The process of gathering and compiling data from various sources is known as data Aggregation. Businesses and groups gather enormous amounts of data from a variety of sources, including social media, customer databases, transactional systems, and many more. What is Data Aggregation?

Process 59

Process Data Mining Aggregated Data Portfolio 59

Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

Systems 80

Systems Raw Data Metadata Data Cleanse 80

Knowledge Hut

JULY 26, 2023

Veracity meaning in big data is the degree of accuracy and trustworthiness of data, which plays a pivotal role in deriving meaningful insights and making informed decisions. This blog will delve into the importance of veracity in Big Data, exploring why accuracy matters and how it impacts decision-making processes.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Knowledge Hut

JANUARY 25, 2024

Let's dive into the top data cleaning techniques and best practices for the future – no mess, no fuss, just pure data goodness! What is Data Cleaning? It involves removing or correcting incorrect, corrupted, improperly formatted, duplicate, or incomplete data. Why Is Data Cleaning So Important?

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

Knowledge Hut

JANUARY 18, 2024

Along with the ETL, data transformation and data modeling options. I've noticed a growing trend of businesses adopting Power BI and Fabric tools to elevate their data capabilities and refine decision-making processes. Before we proceed, let's have a look at what big data is and the types of big data.

BI 52

BI Data Cleanse Business Intelligence Datasets 52

RandomTrees

FEBRUARY 6, 2024

Modernization in Data Engineering with GenAI Generation: The Art of Data Creation: Generative AI has emerged as a potent tool for creating synthetic datasets. Generative AI corrects data imbalances, ensuring fair sentiment analysis on e-commerce platforms, enriches training data for natural language processing (NLP) tasks.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Databand.ai

AUGUST 30, 2023

Building a Winning Data Quality Strategy: Step by Step Eitan Chazbani August 30, 2023 What Is a Data Quality Strategy? A data quality strategy details the processes, tools, and techniques employed to ensure your company’s data is accurate, consistent, complete, and up-to-date.

Building 52

Building Data Cleanse Data Governance Datasets 52

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. Source Code: Stock and Twitter Data Extraction Using Python, Kafka, and Spark 2.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Databand.ai

AUGUST 30, 2023

There are various ways to ensure data accuracy. Data validation involves checking data for errors, inconsistencies, and inaccuracies, often using predefined rules or algorithms. Data cleansing involves identifying and correcting errors, inconsistencies, and inaccuracies in data sets.

Data Integration 52

Data Integration Data Cleanse Data Validation Data Governance 52

Precisely

JULY 17, 2023

Cleansing and enriching data due to inefficient cleansing processes, address data inconsistencies, and limited access to external datasets. Cleansing and enriching data due to inefficient cleansing processes, address data inconsistencies, and limited access to external datasets.

Data Integration 52

Data Integration Data Cleanse Data Governance Government 52

Databand.ai

AUGUST 30, 2023

Data profiling tools: Profiling plays a crucial role in understanding your dataset’s structure and content. This helps you make informed decisions about how best to clean and preprocess this information before using it in downstream processes like analytics or model training.

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

Striim

FEBRUARY 5, 2024

It involves implementing robust measures to safeguard the integrity of data. By ensuring confidentiality and reliability through stringent security protocols, organizations can protect their data from unauthorized access, instilling trust in their data management practices.

Pharmaceutical 52

Pharmaceutical Data Cleanse Metadata Medical 52

Knowledge Hut

JANUARY 30, 2024

Whether you're a seasoned data scientist or just stepping into the world of data, come with me as we unravel the secrets of data extraction and learn how it empowers us to unleash the full potential of data. What is data extraction? What is the purpose of extracting data?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Ascend.io

FEBRUARY 28, 2024

Engineers ensure the availability of clean, structured data, a necessity for AI systems to learn from patterns, make accurate predictions, and automate decision-making processes. Through the design and maintenance of efficient data pipelines , data engineers facilitate the seamless flow and accessibility of data for AI processing.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Striim

FEBRUARY 26, 2024

Organizing, storing, and accessing data is important for AI. Incorporating AI into data modeling relies on fundamental techniques and principles that enhance the synergy between data and AI models. Techniques like outlier detection and imputation help make sure your data is reliable and ready for analysis.

Data Cleanse 52

Data Cleanse Business Intelligence Data Data Integration 52

Edureka

FEBRUARY 8, 2024

Different instance types offer varying levels of compute power, memory, and storage, which directly influence tasks such as data processing, application responsiveness, and overall system throughput. Key Factors to Consider- When choosing an AWS instance type, several key factors should guide your decision-making process.

AWS 52

AWS NoSQL Deep Learning Datasets 52

Knowledge Hut

NOVEMBER 27, 2023

A data scientist’s job needs loads of exploratory data research and analysis on a daily basis with the help of various tools like Python, SQL, R, and Matlab. This role is an amalgamation of art and science that requires a good amount of prototyping, programming and mocking up of data to obtain novel outcomes.

Data Science 52

Data Science Datasets Machine Learning Algorithm 52

Knowledge Hut

OCTOBER 30, 2023

Data Validation: Help validate data against predefined business rules and ensure data quality. Documentation: Maintain documentation for reports, data sources, and data transformation processes. Manage data integration tasks, including data source connections and data transformation processes.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Edureka

AUGUST 2, 2023

Due to its strong data analysis and manipulation skills, it has significantly increased its prominence in the field of data science. Python offers a strong ecosystem for data scientists to carry out activities like data cleansing, exploration, visualization, and modeling thanks to modules like NumPy, Pandas, and Matplotlib.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Knowledge Hut

DECEMBER 22, 2023

Power BI Desktop Power BI Desktop is free software that can be downloaded and installed to build reports by accessing data easily without the need for advanced report designing or query skills to build a report. Multiple Data Sources Multiple Data Sources support various data sources like Excel, CSV, SQL Server, Web files, etc.

BI 98

BI Business Intelligence Machine Learning SQL 98

U-Next

OCTOBER 27, 2022

You might be wondering, “ what is data cleaning?” ” It is an integral part of a process where the data needs to be cleaned before it can be used effectively by any organization or business. In recent times, the importance of data has increased exponentially. What Is Data Cleaning? .

IT 40

IT Data Cleanse Datasets Bytes 40

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. How ELT Works The process of ELT can be broken down into the following three stages: 1.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Knowledge Hut

SEPTEMBER 26, 2023

The insights derived from the data in hand are then turned into impressive business intelligence visuals such as graphs or charts for the executive management to make strategic decisions. In this post, we will discuss the top power BI developer skills required to access Microsoft’s power business intelligence software.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

Monte Carlo

JULY 11, 2023

Look for potential biases, flaws, or limitations in the data collection process. Sample size and representativeness: If the data is based on a sample, assess whether the sample size is large enough to be statistically significant and representative of the target population. is the gas station actually where the map says it is?).

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

Monte Carlo

MARCH 24, 2023

We’ll explore their definitions, purposes, and methods so you can ensure both data integrity and data validity in your organization. What is Data Integrity? Data integrity is the process of maintaining the consistency, accuracy, and trustworthiness of data throughout its lifecycle, including storage, retrieval, and usage.

Data Validation 52

Data Validation Data Integration Data Cleanse Data Pipeline 52

Knowledge Hut

OCTOBER 13, 2023

As per Microsoft, “A Power BI report is a multi-perspective view of a dataset, with visuals representing different findings and insights from that dataset. ” Reports and dashboards are the two vital components of the Power BI platform, which are used to analyze and visualize data.

BI 52

BI Business Analyst Datasets Raw Data 52

Towards Data Science

FEBRUARY 10, 2023

As we move firmly into the data cloud era, data leaders need metrics for the robustness and reliability of the machine–the data pipelines, systems, and engineers–just as much as the final (data) product it spits out. Where do we need to have data streaming vs batch? What data SLAs should we have in place?

Data Pipeline 94

Data Pipeline Data Cleanse Data Machine Learning 94

AltexSoft

MAY 14, 2021

Not only does Big Data apply to the huge volumes of continuously growing data that come in different formats, but it also refers to the range of processes, tools, and approaches used to gain insights from that data. Key Big Data characteristics. Velocity is the speed at which the data is generated and processed.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

JANUARY 18, 2024

By automating processes such as data quality checks and version control, DataOps can improve the accuracy and efficiency of data analytics while also reducing errors. For instance, automating data cleaning and transformation can save time and reduce errors in the data processing stage.

Data Analytics 52

Data Analytics Healthcare Machine Learning Algorithm 52

AltexSoft

AUGUST 29, 2023

Another distinction is the ETL vs. ELT choice: In data warehouses, Extract and Transform processes usually occur before data is loaded into the warehouse. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Cloudera

JANUARY 11, 2021

These devices can be servers, workstations, and laptops but also sensors, self-driving cars, machines in factories, etc, where you want to collect specific data using some of the NiFi features within MiNiFi. The ability to filter, select, and triage the data before sending it to a destination.

Kafka 61

Kafka Java Data Cleanse Datasets 61

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. Snowflake hides user data objects and makes them accessible only through SQL queries through the compute layer.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Monte Carlo

FEBRUARY 7, 2023

As we move firmly into the data cloud era, data leaders need metrics for the robustness and reliability of the machine–the data pipelines, systems, and engineers–just as much as the final (data) product it spits out. Where do we need to have data streaming vs batch ? What data SLAs should we have in place?

Management 72

Management Data Data Pipeline Data Cleanse 72

ProjectPro

JUNE 18, 2015

For Silicon Valley startups launching a big data platform, the best way to reduce expenses is to pay remote workers so that they can distribute tasks to people who have internet access anywhere in the world. Let’s understand how crowdsourcing big data can revolutionize business processes.

Big Data 52

Big Data Process Data Cleanse Data Analytics 52

RandomTrees

NOVEMBER 29, 2023

So, here the argument on what to use and where to use become an important topic to be considered and here we can rather focus on some of the adaptable and sensitive models and we begin to consider the data vaults’ technique. The data from many data bases are sent to the data warehouse through the ETL processes.

Data Warehouse 52

Data Warehouse Data Lake Database-centric Data Cleanse 52

RandomTrees

SEPTEMBER 6, 2020

This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics. The data objects are accessible only through SQL query operations run using Snowflake. Query Processing: Query processing in Snowflake is done using virtual warehouses.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. What do Data Engineers Do? Work closely with software engineers and data scientists.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52