Precisely

APRIL 11, 2023

What existing data does the organization have to support my initiative? Where does that data live? Do I have access to the data? What do I need to do to access the data now and make it easy to find and access in the future? How can I ensure the data is up-to-date and issue-free moving forward?

Accessible 52

Accessible Accessibility Metadata Data Integration 52

Precisely

JANUARY 9, 2023

With global data creation projected to grow to more than 180 zettabytes by 2025 , it’s not surprising that more organizations than ever are looking to harness their ever-growing datasets to drive more confident business decisions. As data initiatives become more sophisticated, organizations will uncover new data quality challenges.

Data Integration 81

Data Integration Data Governance Government Data 81

Precisely

JULY 17, 2023

And trusted data needs data integrity – maximum accuracy, consistency, and context. Cleansing and enriching data due to inefficient cleansing processes, address data inconsistencies, and limited access to external datasets. That’s where the Precisely Data Integrity Suite comes in.

Data Integration 52

Data Integration Data Cleanse Data Governance Government 52

Precisely

MARCH 6, 2023

Read Financial Services ESG Reporting: The essential role of data Financial organizations are now assessing how they can derive more environmental, social and governance insights, while optimizing reporting through their existing infrastructure.

Data Integration 52

Data Integration Government Data Governance Datasets 52

Ascend.io

MAY 23, 2023

A prime example of such patterns is orphaned datasets. These are datasets that exist in a database or data storage system but no longer have a relevant link or relationship to other data, to any of the analytics, or to the main application — making them a deceptively challenging issue to tackle.

Datasets 52

Datasets Data Pipeline Metadata Database 52

AltexSoft

APRIL 21, 2022

But in order to analyze the information correctly and profit from it, you should guarantee data integrity. This article explores what data integrity is, what it is not, and why it’s difficult to achieve the integrity. Also, we dive into data integrity threats and propose countermeasures to them.

Data Integration 59

Data Integration Food Datasets Pharmaceutical 59

Precisely

MARCH 23, 2023

You need a flexible framework to efficiently identify, understand, and link the underlying data elements required for accurate, consistent, and contextualized ESG reporting. In summary: your ESG data needs data integrity. The post Why You Need Data Integrity for ESG Reporting appeared first on Precisely.

Data Integration 52

Data Integration Government High Quality Data Data 52

Precisely

MARCH 14, 2023

New technologies are making it easier for customers to process increasingly large datasets more rapidly. First, private cloud infrastructure providers like Amazon (AWS), Microsoft (Azure), and Google (GCP) began by offering more cost-effective and elastic resources for fast access to infrastructure. So how did providers respond?

Data Integration 52

Data Integration High Quality Data BI Data 52

Databand.ai

JULY 6, 2023

Data Integrity Testing: Goals, Process, and Best Practices Niv Sluzki July 6, 2023 What Is Data Integrity Testing? Data integrity testing refers to the process of validating the accuracy, consistency, and reliability of data stored in databases, data warehouses, or other data storage systems.

Data Integration 52

Data Integration Process Data Validation Data Governance 52

Grouparoo

DECEMBER 7, 2021

Integrity is a critical aspect of data processing; if the integrity of the data is unknown, the trustworthiness of the information it contains is unknown. What is Data Integrity? Data integrity is the accuracy and consistency over the lifetime of the content and format of a data item.

Data Integration 52

Data Integration Manufacturing ETL Tools Transportation 52

Grouparoo

NOVEMBER 5, 2021

The problem is that typically achieving compatibility and interoperability across the entire dataset requires surmounting significant challenges. Companies that can leverage the value embedded within this data will have the best chance of prospering in a competitive and volatile marketplace. What is Data Integration?

Data Integration 40

Data Integration Datasets Data Warehouse Data Consolidation 40

Ascend.io

APRIL 12, 2023

So when we talk about making data usable, we’re having a conversation about data integrity. Data integrity is the overall readiness to make confident business decisions with trustworthy data, repeatedly and consistently. Data integrity is vital to every company’s survival and growth.

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

Monte Carlo

MARCH 24, 2023

However, the data is not valid because the height information is incorrect – penguins have the height data for giraffes, and vice versa. The data doesn’t accurately represent the real heights of the animals, so it lacks validity. What is Data Integrity? How Do You Maintain Data Integrity?

Data Validation 52

Data Validation Data Integration Data Cleanse Data Pipeline 52

Precisely

MAY 16, 2024

Ensure your data is accurate, consistent, and contextualized to enable trustworthy AI systems that avoid biases, improve accuracy and reliability, and boost contextual relevance and nuance. Adopt strategic practices in data integration, quality management, governance, spatial analytics, and data enrichment.

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Amazon Web Services AWS Data Integration Datasets 67

Data Engineering Podcast

MAY 26, 2024

Trusted by the teams at Comcast and Doordash, Starburst delivers the adaptability and flexibility a lakehouse ecosystem promises, while providing a single point of access for your data and all your data governance allowing you to discover, transform, govern, and secure all in one place. Want to see Starburst in action?

Systems 130

Systems Data Lake High Quality Data Google Cloud 130

Grouparoo

AUGUST 24, 2021

The State of Customer Data The Modern Data Stack is all about making powerful marketing and sales decisions and performing impactful business analytics from a single source of truth. Customer Data Integration makes this possible. Building a custom pipeline with a data engineering team can be an exhausting effort.

Data Integration 52

Data Integration Data Consolidation Data Warehouse ETL Tools 52

Ascend.io

DECEMBER 14, 2022

As data became the backbone of most businesses, data integration emerged as one of the most significant challenges. Today, a good part of the job of a data engineer is to move data from one place to another by creating pipelines that can be either ETL vs. ELT. This causes two issues.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

AltexSoft

OCTOBER 8, 2021

What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. The good news is, businesses can choose the path of data integration to make the most out of the available information. Data integration in a nutshell. Data integration process.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Databand.ai

MAY 30, 2023

Data quality can be influenced by various factors, such as data collection methods, data entry processes, data storage, and data integration. Maintaining high data quality is crucial for organizations to gain valuable insights, make informed decisions, and achieve their goals.

Data Cleanse 85

Data Cleanse Datasets Data Governance Data Validation 85

Precisely

MARCH 4, 2024

As you navigate the complexities of integrating AI into your operations, it’s essential to understand data integrity – data with maximum accuracy, consistency, and context – and its pivotal role in ensuring AI reliability. Next, you’ll see valuable AI use cases and how data integrity powers success.

Amazon Web Services 70

Amazon Web Services Data Integration High Quality Data Government 70

ThoughtSpot

MARCH 5, 2024

When created, Snowflake materializes query results into a persistent table structure that refreshes whenever underlying data changes. These tables provide a centralized location to host both your raw data and transformed datasets optimized for AI-powered analytics with ThoughtSpot. Set refresh schedules as needed.

BI 94

BI Datasets Raw Data SQL 94

Data Engineering Weekly

APRIL 7, 2024

We index only top-tier tables, promoting the use of these higher-quality datasets. I strongly believe the concept of Data Product will play a bigger role in data engineering. It is evident that it will become the foundation of trusted sources, which is essential to taking advantage of advancements from LLMs.

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Data Engineering Data Engineer Engineering Unstructured Data 70

RandomTrees

FEBRUARY 6, 2024

Over the years, the field of data engineering has seen significant changes and paradigm shifts driven by the phenomenal growth of data and by major technological advances such as cloud computing, data lakes, distributed computing, containerization, serverless computing, machine learning, graph database, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Volume Big Data refers to large volumes of data, typically in the order of terabytes or petabytes. It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques.

Big Data 52

Big Data Datasets Data Analysis Media 52

Precisely

JANUARY 8, 2024

Location intelligence provides a critical link that joins existing data elements with the geospatial context surrounding them. By understanding where your customers live, for example, you can glean meaningful insights about their income level, lifestyle, and access to services.

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Insurance Telecommunication Retail Data Integration 62

Precisely

JUNE 5, 2023

As more organizations prioritize data-driven decision-making, the pressure mounts for data teams to provide the highest quality data possible for the business. Reach new levels of data quality and deeper analysis – faster So then, what are the options for data practitioners?

Datasets 52

Datasets Data Integration Data Cloud 52

Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Big data offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

APRIL 23, 2024

These abilities are necessary to ensure that data is organized, secure, and readily accessible. A solid foundation in database management enables professionals to deal with large datasets and interpret intricate data structures. This allows businesses to extract valuable insights from their data.

Database 52

Database Management Relational Database SQL 52

Precisely

NOVEMBER 20, 2023

The answers lie in data integrity and the contextual richness of the data that fuels your AI. If machine learning models have been trained on untrustworthy data, fixing the problem can be expensive and time-consuming. Contextual data. Data integrity is multifaceted.

Raw Data 118

Raw Data Insurance Data Retail 118

Knowledge Hut

MARCH 27, 2024

These are the situations where having a lot of data stored in one location and being able to access it quickly are necessary. What is a Data Structure? Using a data structure allows you to efficiently arrange data on a computer. Flexibility: Offers scalability to manage extensive datasets efficiently.

Database 52

Database Algorithm Relational Database PostgreSQL 52

Precisely

SEPTEMBER 25, 2023

What times of the day are busy in the area, and are roads accessible? Data enrichment helps provide a 360 o view which informs better decisions around insuring, purchasing, financing, customer targeting, and more. Together, data validation and enrichment form a powerful combination that delivers even bigger results for your business.

Data Validation 98

Data Validation Process Raw Data Data Cleanse 98

Striim

FEBRUARY 2, 2024

With this new application integration service, users can stream real-time CRM, ERP, Billing, and Payment data from their cloud applications to data warehouses in minutes with zero coding. Instantly unlock the value of your application data through real-time insights, reports, and dashboards for your businesses.

Cloud 52

Cloud Google Cloud Data Integration Data Pipeline 52

Precisely

DECEMBER 8, 2023

In the context of this change, business leaders recognize the pressing need for data-driven decision-making. Without data integrity, however, initiatives to enable data-driven decisions will fail to meet expectations. What is data integrity ? What is Data Governance?

Data Governance 67

Data Governance Government Datasets Programming 67

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

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AWS Scala Metadata Data Lake 98

Data Engineering Weekly

MAY 5, 2024

The motivation for Machine Unlearning is critical from the privacy perspective and for model correction, fixing outdated knowledge, and access revocation of the training dataset. A key thought-provoking moment for me while reading the article is this quote.

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Data Engineering Data Engineer Engineering Google Cloud 67

Towards Data Science

FEBRUARY 6, 2024

As you do not want to start your development with uncertainty, you decide to go for the operational raw data directly. Accessing Operational Data I used to connect to views in transactional databases or APIs offered by operational systems to request the raw data. Does it sound familiar?

Systems 79

Systems Raw Data Metadata Data Cleanse 79

Ascend.io

FEBRUARY 15, 2024

They play a pivotal role in ensuring data consistency, accuracy, and accessibility because they don’t just clone your data once; it’s an ongoing strategy to keep multiple, identical copies of your data in sync across various sources. Why are Data Replication Strategies Important?

Datasets 52

Datasets Database Data Warehouse Data 52