Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. The right data integration solution helps you streamline operations, enhance data quality, reduce costs, and make better data-driven decisions.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Towards Data Science

JANUARY 17, 2024

Parquet vs ORC vs Avro vs Delta Lake Photo by Viktor Talashuk on Unsplash The big data world is full of various storage systems, heavily influenced by different file formats. These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction. schema(schema).load("s3a://mybucket/ten_million_parquet.csv")

Big Data 71

Big Data Data Data Storage SQL 71

Precisely

SEPTEMBER 6, 2023

However, fewer than half of survey respondents rate their trust in data as “high” or “very high.” ” Poor data quality impedes the success of data programs, hampers data integration efforts, limits data integrity causing big data governance challenges.

Data Governance 52

Data Governance Big Data Government Unstructured Data 52

Knowledge Hut

DECEMBER 27, 2023

Accessing and storing huge data volumes for analytics was going on for a long time. But ‘big data’ as a concept gained popularity in the early 2000s when Doug Laney, an industry analyst, articulated the definition of big data as the 3Vs. What is Big Data? Some examples of Big Data: 1.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

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

Striim

AUGUST 31, 2023

Showing how Kappa unifies batch and streaming pipelines The development of Kappa architecture has revolutionized data processing by allowing users to quickly and cost-effectively reduce data integration costs. Stream processors, storage layers, message brokers, and databases make up the basic components of this architecture.

Data Integration 69

Data Integration Architecture Amazon Web Services ETL System 69

Data Engineering Podcast

JULY 28, 2019

For a small number of sources it is a tractable problem, but as the overall complexity of the data ecosystem continues to expand it may be time to identify new ways to tame the deluge of information. In this episode Tim Ward, CEO of CluedIn, explains the idea of eventual connectivity as a new paradigm for data integration.

Data Integration 100

Data Integration Metadata Media Architecture 100

Data Engineering Podcast

JULY 13, 2020

Summary The first stage of every data pipeline is extracting the information from source systems. There are a number of platforms for managing data integration, but there is a notable lack of a robust and easy to use open source option. The Meltano project is aiming to provide a solution to that situation.

Data Integration 100

Data Integration Data Engineering Data Engineer Data 100

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! Everything is about data these days.

Big Data 52

Big Data Hadoop AWS Relational Database 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

Data Engineering Podcast

OCTOBER 5, 2020

Summary Analytical workloads require a well engineered and well maintained data integration process to ensure that your information is reliable and up to date. Building a real-time pipeline for your data lakes and data warehouses is a non-trivial effort, requiring a substantial investment of time and energy.

Data Integration 100

Data Integration Kafka Data Lake Machine Learning 100

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

Data Engineering Podcast

AUGUST 19, 2019

Summary Managing big data projects at scale is a perennial problem, with a wide variety of solutions that have evolved over the past 20 years. Designed as a fully integrated platform to meet the needs of enterprise grade analytics it provides a solution for the full lifecycle of data at massive scale.

Big Data 100

Big Data Hadoop Data Lake Media 100

AltexSoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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 Data Consolidation 40

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

SEPTEMBER 26, 2021

The Big Data industry will be $77 billion worth by 2023. According to a survey, big data engineering job interviews increased by 40% in 2020 compared to only a 10% rise in Data science job interviews. Table of Contents Big Data Engineer - The Market Demand Who is a Big Data Engineer?

Big Data 52

Big Data Data Engineering Data Engineer Engineering 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.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

NOVEMBER 15, 2021

The adaptability and technical superiority of such open-source big data projects make them stand out for community use. As per the surveyors, Big data (35 percent), Cloud computing (39 percent), operating systems (33 percent), and the Internet of Things (31 percent) are all expected to be impacted by open source shortly.

Big Data 52

Big Data Project Metadata Programming Language 52

Precisely

DECEMBER 28, 2023

Read our eBook A Data Integrator’s Guide to Successful Big Data Projects This eBook will guide through the ins and outs of building successful big data projects on a solid foundation of data integration. Interested in learning more about streaming data pipelines for your organization?

Data Pipeline 91

Data Pipeline Building Kafka Big Data 91

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 billion by 2026? How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98

Monte Carlo

MAY 28, 2024

Let’s see what it takes to design an ingestion architecture that ensures reliable, real-time data processing and supports effective decision-making in big data environments. Major cloud vendors also offer their own scalable solutions, ensuring efficient and reliable data flow across various applications and platforms.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Precisely

OCTOBER 16, 2023

Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. For organizations that continue to rely on mainframe systems to process their most mission-critical workloads, the digital revolution demands new approaches to integration.

Cloud 70

Cloud Cloud Computing Metadata Data Governance 70

ProjectPro

JULY 3, 2015

There are some tech buzzwords like SAP that have been more predominant than “Big Data” Companies can analyse structured big data in real time with in-memory technology. What follows is an elaborate explanation on how SAP and Hadoop together can bring in novel big data solutions to the enterprise.

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 40

Knowledge Hut

MARCH 28, 2024

Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance. Develop data models, data governance policies, and data integration strategies. Experience with Azure services for big data processing and analytics.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Precisely

MARCH 9, 2023

Data lakes are often preferred for storing semi-structured data (such as XML files) and unstructured data (such as natural language text). Snowflake, for example, is a SaaS-based data warehouse application that is ideally for storing large volumes of data in the cloud, making it available for analytics.

Data Lake 57

Data Lake Data Warehouse Hadoop Raw Data 57

Precisely

JULY 27, 2023

The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, delivers groundbreaking insights into the importance of trusted data. Let’s explore more of the report’s findings around the challenges and impacts of poor data quality.

Data Programming 52

Data Programming Programming High Quality Data Data Integration 52

Precisely

DECEMBER 21, 2022

With high-quality data at their fingertips, healthcare providers can capitalize on the massive potential surrounding big data. There are a variety of ways big data can help improve patient care while also maximizing value and minimizing costs, but a few in particular stand out among the rest.

Insurance 52

Insurance Data Governance Healthcare High Quality Data 52

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.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Precisely

SEPTEMBER 7, 2023

Advanced data analytics enable insurance carriers to evaluate risk at a far more granular level than ever before, but big data can only deliver real business value when carriers ensure data integrity. Data quality is critical, but data integrity goes much further than accuracy, completeness, and consistency.

Insurance 52

Insurance Data Integration Data Government 52

Databand.ai

AUGUST 30, 2023

By using DataOps tools, organizations can break down silos, reduce time-to-insight, and improve the overall quality of their data analytics processes. DataOps tools can be categorized into several types, including data integration tools, data quality tools, data catalog tools, data orchestration tools, and data monitoring tools.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Knowledge Hut

DECEMBER 29, 2023

Data scientists may improve their knowledge and response to crucial business demands by opting to specialize in a subfield of their subject. It's possible they'll zero down on a certain data kind, like Big Data, or a computer language. Knowing which data to utilize, how to arrange the data, and so on is essential.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

SEPTEMBER 25, 2023

They are moving their servers and on-premises data to Azure Cloud. What does all of this mean for Data Engineering professionals? In order to manage big data and other operational services, businesses are continuously in need of data engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Towards Data Science

FEBRUARY 16, 2024

Strategically enhancing address mapping during data integration using geocoding and string matching Many individuals in the big data industry may encounter the following scenario: Is the acronym “TIL” equivalent to the phrase “Today I learned” when extracting these two entries from distinct systems?

Food 63

Food Data Ingestion Python Data Science 63

Precisely

DECEMBER 20, 2022

Read more > #4 4 Real-World Examples of Financial Institutions Making Use of Big Data Big data has moved beyond “new tech” status and into mainstream use. Within the financial industry, there are some specialized uses for data integration and big data analytics.

Data Governance 52

Data Governance Government Hadoop Big Data 52

Knowledge Hut

NOVEMBER 2, 2023

Azure Data Catalog for Data Governance and Discovery Azure Data Catalog can be used to catalog and manage information for diverse data assets, allowing for more efficient data governance, data discovery, and data lineage tracing. Aptitude for learning new big data techniques and technologies.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52