The Modern Data Company

JANUARY 22, 2024

The Modern Data Company has been given an honorable mention in Gartner’s 2023 Magic Quadrant for Data Integration. This capability is instrumental in meeting the analytical demands of various data applications, including analytics, business intelligence (ABI), and data science.

Data Integration 87

Data Integration Metadata Government Unstructured Data 87

Data Engineering Podcast

MAY 1, 2022

Summary The predominant pattern for data integration in the cloud has become extract, load, and then transform or ELT. Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today!

Data Warehouse 100

Data Warehouse Data Integration Cloud Google Cloud 100

RandomTrees

AUGUST 22, 2024

Future Trends in Business Intelligence Business intelligence (BI) continues to evolve rapidly, driven by technological advancements and changing business needs. Artificial Intelligence and Machine Learning Integration AI and machine learning are becoming increasingly central to BI solutions.

Business Intelligence 52

Business Intelligence BI Data Preparation Machine Learning 52

Knowledge Hut

JANUARY 19, 2024

Business Intelligence Analyst Importance The proliferation of IoT-connected objects, IoT-based sensors, rising internet usage, and sharp increases in social media activity are all enhancing businesses' ability to gather enormous amounts of data. What Does a Business Intelligence Analyst Do?

Business Intelligence 52

Business Intelligence BI Business Analyst Finance 52

Knowledge Hut

JUNE 28, 2023

The answer lies in the strategic utilization of business intelligence for data mining (BI). Data Mining vs Business Intelligence Table In the realm of data-driven decision-making, two prominent approaches, Data Mining vs Business Intelligence (BI), play significant roles.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

Edureka

FEBRUARY 18, 2023

This is where business intelligence (BI) comes into play. BI can help organizations turn raw data into meaningful insights, enabling better decision-making, optimizing operations, enhancing customer experiences, and providing a strategic advantage. How BI Processes Data? Conclusion What is business intelligence?

Business Intelligence 52

Business Intelligence BI SQL Data Analysis 52

FreshBI

NOVEMBER 21, 2023

FreshBI stands out in this arena, bridging the gap between raw data and actionable insights. FreshBI has made its mark in the realm of business intelligence, offering a unique blend of consultancy services and state-of-the-art BI apps. Businesses no longer need to grapple with overwhelming amounts of data.

Business Intelligence 52

Business Intelligence Hospitality BI Consulting 52

Snowflake

JANUARY 23, 2023

Marketing data integration is the process of combining marketing data from different sources to create a unified and consistent view. If you’re running marketing campaigns on multiple platforms—Facebook, Instagram, TikTok, email—you need marketing data integration. What Problems does Data Integration Solve?

Data Integration 74

Data Integration Data Data Warehouse Cloud 74

Ascend.io

OCTOBER 28, 2024

It is important to note that normalization often overlaps with the data cleaning process, as it helps to ensure consistency in data formats, particularly when dealing with different sources or inconsistent units. Data Validation Data validation ensures that the data meets specific criteria before processing.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Grouparoo

DECEMBER 7, 2021

Organizations collect and leverage data on an ever-expanding basis to inform business intelligence and optimize practices. Data allows businesses to gain a greater understanding of their suppliers, customers, and internal processes. What is Data Integrity? Why is Data Integrity Important?

Data Integration 52

Data Integration Manufacturing ETL Tools Transportation 52

Striim

JUNE 18, 2024

In today’s fast-paced world, staying ahead of the competition requires making decisions informed by the freshest data available — and quickly. That’s where real-time data integration comes into play. What is Real-Time Data Integration + Why is it Important? Why is Real-Time Data Integration Important?

Data Integration 52

Data Integration Data Lake Retail Healthcare 52

ProjectPro

SEPTEMBER 26, 2014

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. Big data, multi-structured data, and advanced analytics.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

Precisely

MARCH 14, 2023

And the desire to leverage those technologies for analytics, machine learning, or business intelligence (BI) has grown exponentially as well. Deploy, execute, and scale natively in modern cloud architectures To meet the need for data quality in the cloud head on, we’ve developed the Precisely Data Integrity Suite.

Data Integration 52

Data Integration High Quality Data BI Data 52

RandomTrees

MARCH 10, 2025

Key Components of an Effective Predictive Analytics Strategy Clean, high-quality data: Predictive analytics is only as effective as the data it analyses. Companies must ensure that their data is accurate, relevant, and up to date to provide useful insights.

Retail 52

Retail Data Governance Hospitality Banking 52

Snowflake

JUNE 5, 2024

Here are the 2024 winners by category: Industry AI Data Cloud Partners: Financial Services AI Data Cloud Services Partner of the Year: EY Healthcare & Life Sciences AI Data Cloud Services Partner of the Year: Hakkoda Healthcare & Life Sciences AI Data Cloud Product Partner of the Year: IQVIA Media and Entertainment AI Data Cloud Services Partner (..)

Entertainment 124

Entertainment Manufacturing Retail Healthcare 124

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

Striim

MARCH 21, 2025

In this post, we’ll share why Change Data Capture is ideal for near-real-time business intelligence and cloud migrations, and four different Change Data Capture methods. What is Change Data Capture? Data can be extracted using database queries (batch-based) or Change Data Capture (near-real-time).

IT 52

IT Data Lake Data Warehouse Relational Database 52

Data Engineering Weekly

FEBRUARY 2, 2025

Shifting left involves moving data processing upstream, closer to the source, enabling broader access to high-quality data through well-defined data products and contracts, thus reducing duplication, enhancing data integrity, and bridging the gap between operational and analytical data domains.

Data Engineering 57

Data Engineering Data Engineer Engineering Data Lake 57

Maxime Beauchemin

JANUARY 20, 2017

I joined Facebook in 2011 as a business intelligence engineer. By the time I left in 2013, I was a data engineer. Instead, Facebook came to realize that the work we were doing transcended classic business intelligence. I wasn’t promoted or assigned to this new role.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

AltexSoft

SEPTEMBER 10, 2021

To get a single unified view of all information, companies opt for data integration. In this article, you will learn what data integration is in general, key approaches and strategies to integrate siloed data, tools to consider, and more. What is data integration and why is it important?

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

Grouparoo

NOVEMBER 5, 2021

Companies that can leverage the value embedded within this data will have the best chance of prospering in a competitive and volatile marketplace. This situation is where a data integration process will help. What is Data Integration? In essence, it is integrating data from multiple sources.

Data Integration 40

Data Integration Datasets Data Warehouse Big Data 40

Zalando Engineering

SEPTEMBER 20, 2015

Yet the monolith does present one advantage: Its consolidation of data in a single place makes business intelligence fairly simple. The more modular your enterprise application becomes, the more work you have to do to bring all of your data together. We will update you as our work progresses!

Data Integration 40

Data Integration PostgreSQL Amazon Web Services Kafka 40

DataKitchen

NOVEMBER 5, 2024

Finally, the Gold laye r represents the pinnacle of the Medallion architecture, housing fully refined, aggregated, and analysis-ready data. Data is typically organized into project-specific schemas optimized for business intelligence (BI) applications, advanced analytics, and machine learning.

Architecture 78

Architecture Raw Data Pipeline-centric Data Ingestion 78

Maxime Beauchemin

AUGUST 28, 2017

It’s the task of the business intelligence (now data engineering) teams to solve these issues with methodologies that enforces consensus, like Master Data Management (MDM), data integration , and an ambitious data warehousing program.

Data Engineering 174

Data Engineering Data Engineer Engineering Software Engineering 174

Monte Carlo

JULY 30, 2024

Table of Contents What are Data Quality Dimensions? What are the 7 Data Quality Dimensions? Data Accuracy Data Completeness Data Timeliness Data Uniqueness Data Validity Data Integrity Monitor your Data Quality with Monte Carlo What are Data Quality Dimensions?

Data Validation 96

Data Validation Datasets Medical Raw Data 96

Precisely

JANUARY 15, 2024

The Data Quality Mandate More and more business leaders are coming to understand the strategic value of data in the insights that can be extracted from it using artificial intelligence/machine learning and modern business intelligence tools.

Data Validation 114

Data Validation Database Business Intelligence Data Integration 114

Cloudera

DECEMBER 1, 2023

Governments must ensure that the data used for training AI models is of high quality, accurately representing the diverse range of scenarios and demographics it seeks to address. It is vital to establish stringent data governance practices to maintain data integrity, privacy, and compliance with regulatory requirements.

Building 109

Building Government Transportation Data Governance 109

Data Engineering Podcast

JANUARY 1, 2022

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today! Start trusting your data with Monte Carlo today! What is the main challenge now?

Data Warehouse 100

Data Warehouse SQL Hadoop Data Lake 100

Data Engineering Podcast

DECEMBER 25, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value.

Building 100

Building Metadata Business Intelligence Data Lake 100

Data Engineering Podcast

NOVEMBER 20, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Precisely

SEPTEMBER 25, 2023

Read Turning Raw Data into Meaningful Insights Even though organizations value data-driven decision-making more than ever before, data quality remains a major barrier across industries. So how does the data validation process help on the journey to better data quality and ultimately, data integrity?

Data Validation 100

Data Validation Process Raw Data Data Cleanse 100

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer in the Data Science team is responsible for this sort of data manipulation. Big Data is a part of this umbrella term, which encompasses Data Warehousing and Business Intelligence as well. A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

phData: Data Engineering

FEBRUARY 21, 2025

A data warehouse acts as a single source of truth for an organization’s data, providing a unified view of its operations and enabling data-driven decision-making. A data warehouse enables advanced analytics, reporting, and business intelligence. Data integrations and pipelines can also impact latency.

Cloud 52

Cloud Data Warehouse Amazon Web Services Data Ingestion 52

Cloudera

NOVEMBER 19, 2020

Cloudera Data Platform (CDP) is a solution that integrates open-source tools with security and cloud compatibility. Governance: With a unified data platform, government agencies can apply strict and consistent enterprise-level data security, governance, and control across all environments.

Government 119

Government Machine Learning Algorithm Raw Data 119

Towards Data Science

DECEMBER 4, 2023

Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g. Data Lake & Data Integration We’ll face our first challenge while we integrate and consolidate everything in a single place.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Lake 98

Data Engineering Podcast

JANUARY 15, 2022

Summary Applications of data have grown well beyond the venerable business intelligence dashboards that organizations have relied on for decades. StreamSets DataOps Platform is the world’s first single platform for building smart data pipelines across hybrid and multi-cloud architectures.

Engineering 100

Engineering Electronics Data Pipeline ETL Tools 100

Data Engineering Weekly

MAY 26, 2024

[link] Tweeq: Tweeq Data Platform: Journey and Lessons Learned: Clickhouse, dbt, Dagster, and Superset Tweeq writes about its journey of building a data platform with cloud-agnostic open-source solutions and some integration challenges. It is refreshing to see an open stack after the Hadoop era.

Data Engineering 76

Data Engineering Data Engineer Engineering Google Cloud 76