Siphiwe  Nair

Siphiwe Nair

1624185000

Top 10 Companies Hiring Data Engineering Professionals

Analytics Insight has listed top 10 companies hiring data engineering professionals with a decent salary

Over the past few years, the usage of data has exploded drastically. More people, organizations, businesses, etc. are availing data as part of their routine mechanism. Earlier, people focused more on useful insights and analysis, but now, they have come to the sense that managing data also needs equal importance. As a result, the role of data engineer has ballooned in the technology sector. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. Data engineers are responsible for finding trends in datasets and developing algorithms to help make raw data more useful to the enterprise. The Dice 2020 Tech Job Report labeled data engineering as the fastest-growing job of 2019, with a 50% year-over-year growth in the number of openings. According to Dataquest, data engineers performs three main roles namely generalist (found in small teams or small companies), pipeline-centric (found in midsize companies) and database-centric (works in large organizations). Analytics Insight has figured top 10 companies hiring data engineering professionals with decent salary.

#big data #latest news #top 10 companies hiring data engineers #top 10 companies hiring data engineering professionals #data engineer jobs. #top companies hiring data engineering professionals

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Top 10 Companies Hiring Data Engineering Professionals
Siphiwe  Nair

Siphiwe Nair

1624185000

Top 10 Companies Hiring Data Engineering Professionals

Analytics Insight has listed top 10 companies hiring data engineering professionals with a decent salary

Over the past few years, the usage of data has exploded drastically. More people, organizations, businesses, etc. are availing data as part of their routine mechanism. Earlier, people focused more on useful insights and analysis, but now, they have come to the sense that managing data also needs equal importance. As a result, the role of data engineer has ballooned in the technology sector. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. Data engineers are responsible for finding trends in datasets and developing algorithms to help make raw data more useful to the enterprise. The Dice 2020 Tech Job Report labeled data engineering as the fastest-growing job of 2019, with a 50% year-over-year growth in the number of openings. According to Dataquest, data engineers performs three main roles namely generalist (found in small teams or small companies), pipeline-centric (found in midsize companies) and database-centric (works in large organizations). Analytics Insight has figured top 10 companies hiring data engineering professionals with decent salary.

#big data #latest news #top 10 companies hiring data engineers #top 10 companies hiring data engineering professionals #data engineer jobs. #top companies hiring data engineering professionals

Ian  Robinson

Ian Robinson

1624399200

Top 10 Big Data Tools for Data Management and Analytics

Introduction to Big Data

What exactly is Big Data? Big Data is nothing but large and complex data sets, which can be both structured and unstructured. Its concept encompasses the infrastructures, technologies, and Big Data Tools created to manage this large amount of information.

To fulfill the need to achieve high-performance, Big Data Analytics tools play a vital role. Further, various Big Data tools and frameworks are responsible for retrieving meaningful information from a huge set of data.

List of Big Data Tools & Frameworks

The most important as well as popular Big Data Analytics Open Source Tools which are used in 2020 are as follows:

  1. Big Data Framework
  2. Data Storage Tools
  3. Data Visualization Tools
  4. Big Data Processing Tools
  5. Data Preprocessing Tools
  6. Data Wrangling Tools
  7. Big Data Testing Tools
  8. Data Governance Tools
  9. Security Management Tools
  10. Real-Time Data Streaming Tools

#big data engineering #top 10 big data tools for data management and analytics #big data tools for data management and analytics #tools for data management #analytics #top big data tools for data management and analytics

Siphiwe  Nair

Siphiwe Nair

1624072920

10 Must-have Skills for Data Engineering Jobs

Big data skills are crucial to land up data engineering job roles. From designing, creating, building, and maintaining data pipelines to collating raw data from various sources and ensuring performance optimization, data engineering professionals carry a plethora of tasks. They are expected to know about big data frameworks, databases, building data infrastructure, containers, and more. It is also important that they have hands-on exposure to tools such as Scala, Hadoop, HPCC, Storm, Cloudera, Rapidminer, SPSS, SAS, Excel, R, Python, Docker, Kubernetes, MapReduce, Pig, and to name a few.

Here, we list some of the important skills that one should possess to build a successful career in big data.

1. Database Tools
2. Data Transformation Tools
3. Data Ingestion Tools
4. Data Mining Tools

#big data #latest news #data engineering jobs #skills for data engineering jobs #10 must-have skills for data engineering jobs #data engineering

Siphiwe  Nair

Siphiwe Nair

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Gerhard  Brink

Gerhard Brink

1621413060

Top 5 Exciting Data Engineering Projects & Ideas For Beginners [2021]

Data engineering is among the core branches of big data. If you’re studying to become a data engineer and want some projects to showcase your skills (or gain knowledge), you’ve come to the right place. In this article, we’ll discuss data engineering project ideas you can work on and several data engineering projects, and you should be aware of it.

You should note that you should be familiar with some topics and technologies before you work on these projects. Companies are always on the lookout for skilled data engineers who can develop innovative data engineering projects. So, if you are a beginner, the best thing you can do is work on some real-time data engineering projects.

We, here at upGrad, believe in a practical approach as theoretical knowledge alone won’t be of help in a real-time work environment. In this article, we will be exploring some interesting data engineering projects which beginners can work on to put their data engineering knowledge to test. In this article, you will find top data engineering projects for beginners to get hands-on experience.

Amid the cut-throat competition, aspiring Developers must have hands-on experience with real-world data engineering projects. In fact, this is one of the primary recruitment criteria for most employers today. As you start working on data engineering projects, you will not only be able to test your strengths and weaknesses, but you will also gain exposure that can be immensely helpful to boost your career.

That’s because you’ll need to complete the projects correctly. Here are the most important ones:

  • Python and its use in big data
  • Extract Transform Load (ETL) solutions
  • Hadoop and related big data technologies
  • Concept of data pipelines
  • Apache Airflow

#big data #big data projects #data engineer #data engineer project #data engineering projects #data projects