Precisely

JULY 17, 2023

Cleansing and enriching data due to inefficient cleansing processes, address data inconsistencies, and limited access to external datasets. While each presents its own challenges, they all make it difficult to effectively leverage data for strong, agile decision-making. How many of these resonate with you?

Data Integration 52

Data Integration Data Cleanse Data Governance Government 52

Databand.ai

AUGUST 30, 2023

8 Data Quality Monitoring Techniques & Metrics to Watch Niv Sluzki August 30, 2023 What Is Data Quality Monitoring? Data quality monitoring refers to the assessment, measurement, and management of an organization’s data in terms of accuracy, consistency, and reliability.

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Knowledge Hut

JULY 26, 2023

This blog will delve into the importance of veracity in Big Data, exploring why accuracy matters and how it impacts decision-making processes. It is important to note that developing expertise in Big Data can significantly enhance your understanding and proficiency in dealing with veracity challenges.

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Big Data Data Cleanse Retail Healthcare 52

Databand.ai

JULY 19, 2023

However, the ultimate goal is simple: to prepare data for immediate use. Whether it is intended for analytics purposes, application development, or machine learning, the aim of data ingestion is to ensure that data is accurate, consistent, and ready to be utilized. In this article: Why Is Data Ingestion Important?

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Data Ingestion Process Data Cleanse Data Governance 52

Databand.ai

AUGUST 30, 2023

DataOps is often likened to the DevOps and agile methodologies used in software development, as it aims to break down silos, encourage collaboration, and streamline workflows for data teams. The core philosophy of DataOps is to treat data as a valuable asset that must be managed and processed efficiently.

Data Governance 52

Data Governance Data Pipeline Government Data Cleanse 52

Cloudera

JUNE 22, 2023

These dis-integrated resources are “data platforms” in name only: in addition to their high maintenance costs, their lack of interoperability with other critical systems makes it difficult to respond to business change. The top-line benefits of a hybrid data platform include: Cost efficiency. Simplified compliance. Flexibility.

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Data Cleanse Data Governance Unstructured Data Cloud Storage 66

Databand.ai

JULY 19, 2023

A Beginner’s Guide [SQ] Niv Sluzki July 19, 2023 ELT is a data processing method that involves extracting data from its source, loading it into a database or data warehouse, and then later transforming it into a format that suits business needs. This transformation could involve cleaning, aggregating, or summarizing the data.

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Data Cleanse Raw Data Data Storage Data Warehouse 52

RandomTrees

FEBRUARY 6, 2024

Transformation: Shaping Data for the Future: LLMs facilitate standardizing date formats with precision and translation of complex organizational structures into logical database designs, streamline the definition of business rules, automate data cleansing, and propose the inclusion of external data for a more complete analytical view.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

OCTOBER 30, 2023

For any organization to grow, it requires business intelligence reports and data to offer insights to aid in decision-making. This data and reports are generated and developed by Power BI developers. The work of a Power BI developer is to take data in its raw form, derive meaning, and make sense of it.

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Databand.ai

AUGUST 30, 2023

Integrating these principles with data operation-specific requirements creates a more agile atmosphere that supports faster development cycles while maintaining high quality standards. This demands the implementation of advanced data integration techniques, such as real-time streaming ingestion, batch processing, and API-based access.

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Data Governance Data Cleanse Government Data Pipeline 40

AltexSoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. What is a data lake? Who needs a data lake?

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Data Lake Architecture IT Amazon Web Services 52

Databand.ai

AUGUST 30, 2023

Accelerated Data Analytics DataOps tools help automate and streamline various data processes, leading to faster and more efficient data analytics. Enhanced Data Quality Data quality is a critical factor in the success of data analytics projects. Genie manages and allocates resources for big data jobs.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 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.

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ProjectPro

FEBRUARY 8, 2023

ETL developer is a software developer who uses various tools and technologies to design and implement data integration processes across an organization. The role of an ETL developer is to extract data from multiple sources, transform it into a usable format and load it into a data warehouse or any other destination database.

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ETL Tools Data Cleanse Data Warehouse Big Data 52

Knowledge Hut

JANUARY 18, 2024

From social media posts and online transactions to sensor readings and healthcare records, data is the fuel that powers modern businesses and organizations. But here's the fascinating part - it's estimated that by 2025, a whopping 463 exabytes of data will be created globally every single day.

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Data Analytics Healthcare Machine Learning Algorithm 52

ProjectPro

JANUARY 27, 2023

Whether you are a data engineer, BI engineer, data analyst, or an ETL developer, understanding various ETL use cases and applications can help you make the most of your data by unleashing the power and capabilities of ETL in your organization. You have probably heard the saying, "data is the new oil". Well, it surely is!

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BI ETL Tools Retail Healthcare 52

Monte Carlo

JULY 11, 2023

A key component of data quality is data accuracy – in fact, it’s one of the 6 overarching dimensions of data quality. Every day, your company relies on data to make all kinds of decisions: about pricing, about product development, about messaging strategy. is the gas station actually where the map says it is?).

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Data Cleanse Datasets Data Governance Government 40

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. Operational : Data used directly in support of business operations in near-real time.

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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 Data Cleanse 52

Monte Carlo

FEBRUARY 7, 2023

At Monte Carlo, we like to think of data quality management within the context of physical fitness. No technology, including data observability , can act as a slimming belt toning your data quality while you lay back and relax. Operational : Data used directly in support of business operations in near-real time.

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Management Data Data Pipeline Data Cleanse 72

Databand.ai

JUNE 20, 2023

Data integrity refers to the overall accuracy, consistency, and reliability of data stored in a database, data warehouse, or any other information storage system. It is a critical aspect of data management, ensuring that the information used by an organization is correct, up-to-date, and fit for its intended purpose.

Data Integration 52

Data Integration Data Validation Pharmaceutical Data Cleanse 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.

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BI Business Intelligence Raw Data Data Analysis 52

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.

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Cloud Storage Google Cloud Amazon Web Services Data Storage 52

phData: Data Engineering

JULY 18, 2023

The Ultimate Modern Data Stack Migration Guide phData Marketing July 18, 2023 This guide was co-written by a team of data experts, including Dakota Kelley, Ahmad Aburia, Sam Hall, and Sunny Yan. Imagine a world where all of your data is organized, easily accessible, and routinely leveraged to drive impactful outcomes.

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Data Warehouse Pipeline-centric Government Data 52

ProjectPro

AUGUST 24, 2021

Most of us have observed that data scientist is usually labeled the hottest job of the 21st century, but is it the only most desirable job? For beginners or peeps who are utterly new to the data industry, Data Scientist is likely to be the first job title they come across, and the perks of being one usually make them go crazy.

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