#Data Engineers | Explore Tumblr Posts and Blogs

atbravyn · 9 months

Text

#big data #funny #software development #data engineers #coding

2 notes · View notes

technosafar · 1 year

Text

Best Data Scientist Course | Salary | Fees in 2023

Data science has made technology even simpler and easier. With the advance of data science, machine learning has also become quite simple. Do you also want to make a career in data science and want to know how to become a data scientist and how to achieve success in this field? Come, let us know in detail in this blog how to become a data scientist.

Read More About Data Science and how to Become

#datascience #datascientist #digital marketing #data engineers

2 notes · View notes

no--greater--burden · 1 year

Text

27 || nonbinary || they/them || bisexual af || INFJ || 🔞 minors DNI 🔞 ||

sortof an oddball with a creative mind and a logical spirit. a nonbinary person who also has boobs - it is what it is.

if you or your blog display values that are harmful to the safety/lives of others, i will block you.

if you do not: employ empathy, understand that kindness is a choice, or believe that being intentional is important - do not interact with me.

take a look around, be kind, and respect boundaries.

take care out there. 😘

#nonbinary cuties #no--greater--burden #Lara #27 #nonbinary #data engineers #bookworm #hiker #nature enthusiast #homebody #sunset appreciator #stoner #sub leaning switch #d/s switch #painter #creative #musician #pluviophile #cinephile

2 notes · View notes

elizabetholevia · 3 days

Text

$2000000 Worth Of Hair Extensions Sold Using This Facebook Ad Set Up

$2000000 Worth Of Hair Extensions Sold Using This Facebook Ad Set Up $2,000,000 Worth Of Hair Extensions Sold Using This Facebook Ad Set Up https://i3.ytimg.com/vi/zA3wNjI8i80/hqdefault.jpghttps://www.youtube.com/watch?v=zA3wNjI8i80 https://igrowsalons.weebly.com/i-grow-salons/2000000-worth-of-hair-extensions-sold-using-this-facebook-ad-set-up2791454

View On WordPress

#Big Data #Creative Engineer #Data Engineers #Distributed Systems #Software Development #Software Engineering

0 notes

techinfotrends · 25 days

Text

Data Engineering Fueling the Internet of Things (IoT) Revolution

The Internet of Things (IoT) is rapidly transforming our world, with billions of connected devices generating a constant stream of data. But this data deluge is meaningless without the power of data engineering.

Data engineers are the architects behind the scenes, building the infrastructure that collects, processes, and analyzes this vast amount of information. According to a recent study by Gartner, by 2025, there will be over 25 billion connected devices generating data. Data engineers are crucial in ensuring this data is usable, enabling businesses to unlock the true potential of IoT.

Here's how data engineering fuels the IoT revolution:

Data Ingestion: Data engineers design pipelines to efficiently collect data from diverse IoT devices, often with varying formats and communication protocols.

Data Storage and Management: They build robust and scalable data storage solutions (cloud-based or on-premise) to handle the ever-growing volume of data.

Data Cleaning and Preprocessing: Raw IoT data can be noisy and incomplete. Data engineers clean and transform the data to ensure its accuracy and usefulness for analysis.

Data Analytics Integration: The prepared data is then integrated with analytics tools, allowing data scientists to extract valuable insights for predictive maintenance, optimizing operations, and developing innovative data-driven products and services.

Data engineering is the backbone of the IoT revolution, transforming raw data into actionable intelligence that fuels smarter cities, efficient industries, and a more connected future.

USDSI® presents a detailed guide on how data engineering effectively handles various challenges posed by huge amount of data generated by IoT along with applications of data engineering in IoT.

So, check out now and grab your copy for a detailed overview.

So, download your copy now and learn the synergy between Data engineering and IoT.

#Data engineers

0 notes

tommatt12 · 9 months

Text

#data engineers #database #data analytics #big data analytics #machine learning #bootcamp

1 note · View note

waywardfestivalrebel-blog · 9 months

Text

Is data engineering a promising career for India's technical background students?

The demand for big data professionals has noway advanced. Numerous people are erecting high-payment careers working with big data. Data wisdom is heavily calculation-acquainted. By discrepancy, data masterminds work primarily on the tech side, erecting data channels. The two places have in common that both work with big data. Working with big data frequently takes a big platoon. Data masterminds work with people in roles like data storehouse masterminds, data platform masterminds, data structure masterminds, analytics masterminds, data masterminds, and DevOps masterminds.

Data engineers bridge the gap between software engineering and data wisdom and transfigure data into a useful format for analysis. Let us take an illustration; a data scientist wants to dissect Uber and one of its challengers by checking a user action history compared to the competition and see what conduct relates to druggies who spend further. We should combine information from the garçon access logs and the app event logs to enable them to produce this. Both Uber and its competition are generating huge quantities of data from their mobile app( from riders and motorists).

A data mastermind will produce a channel that will read the mobile app and garçon logs in real-time, parse them, and attaches them to a specific user. It should be a bus-spanning one so that it can accommodate a large number of users.

Steps to Become a Data Engineer

Becoming a Data engineer requires education, practical experience, and nonstop literacy. Following are the ways to pursue a career as a Data engineer.

Step 1:- Earn a Graduation Degree

After clearing class 12, candidates should look to enroll in a UG program fastening on data wisdom and engineering generalities. Some majors that campaigners can pursue include Data Science, Computer Science, Mathematics, Statistics, and Information Technology.

Step 2:- Develop Data Engineering Skills

Data engineering is constantly evolving. The candidates should learn skills to keep up with the trend. Data masterminds should retain a set of specialized and soft chops to exceed in their places.

Step 3:- Gain Hands-on Experience

Candidates should apply for externships to work on different systems and develop the skills needed to be a Data engineer. Internships also help in generating a good portfolio.

Step 4:- Develop a Data Engineering Portfolio

A portfolio is important to demonstrate fresher skills and an understanding of generalities to implicit employers. Candidates should start working on their portfolios by participating in freelance work and structuring sample systems.

Step 5:- Launch application for Data Engineer jobs

After completing their education and gaining significant skills, candidates should choose Data engineer positions and offer services. Candidates can also conclude postgraduate courses for better career openings.

Facts about a Career in Data Engineering

A Strong Developer

It is pivotal for a data engineer to have a strong programming background. They also need a love of or at least an interest in data, in changing patterns in data, or else they may find the work boring. Also, they like and can produce systems that are delicate and complex. Big data systems are more complex than small data.

Technology Knowledge

Most universities are tutoring programming from an academic point of view, and there is a difference between what the assiduity wants and what academia is furnishing. A university may have classes on programming, but people who want to become data engineers may have to learn the specialized and systems side on their own. A good data engineer values the right tool for the job. Data engineers need to know 10 to 30 different technologies to choose the right tool for the job in technologies. Data masterminds will inescapably need to collude out their channel infrastructures in a clear and presentable way.

Experience versus Education

Anyone with a software background having experience in operations or systems can make a smooth transition to data engineering. Training in software development and data science skills, statistics, and calculation are important. Data negotiating teams generally dispose toward seniors. More astronomically grounded software engineering brigades will have people with a wider range of experience.

Social and Communication Skills

Data quality is extremely crucial when building channels. All downstream work is only as good as the quality and integrity of the data you are moving through the channel. A good data engineer should appreciate the fineness of clean and simple designs that are not over-architected. A good data engineer should find satisfaction in helping their guests break through painful problems.

Typical Earnings of a Data Mastermind

Data engineering is supposed to be the best-paying job in tech and will grow exponentially in the coming times as data explodes and demand for professed professionals increases.

Dices’ 2020 Tech report listed data engineering as the swift-growing job of 2019, growing by 50 times over time. This trend is only going overhead in the coming decades.

According to Glassdoor, the estimated total pay for a data engineer is $118,015 per time in the United States, with an average payment of $97,820 per time. But this is only a median estimate, of course. Our earnings could be advanced or lower depending on numerous factors, including position, cost of living, etc.

Conclusion

The data structure is necessary for any company looking for data mining ways and gain practicable perceptivity. Numerous of the new data engineers in the industry came from a background in software engineering and brought to this field their skills in Linux, Java, SQL, Python, and Hadoop. As this career continues to grow and change, data engineers can gain influence by staying in the van of advances in data operation.

Learn Data Engineering from the comfort of your home from LEJHRO Data Engineering Bootcamp. Get the benefits of personalized mentorship training, soft skills development, extensive career support, and an agile driven-learning approach at a very reasonable price. Register Now.

#data engineers #engineering

0 notes

manoj-321 · 9 months

Text

SG Analytics - While ChatGPT is a powerful tool that can be used in data engineering, it cannot replace the expertise of a data engineer. Data engineering requires a deep understanding which ChatGPT cannot replicate.

#Data engineers #ChatGPT Replace Data Engineers #AI data engineer #Chatgpt data engineering #esg services #esg data and analytics

0 notes

jobtise1 · 9 months

Text

#jobs hiring #tech jobs #usa jobs #data engineers #data scientist #indiajobs #full time jobs #remote jobs #remote work

0 notes

workoffice23 · 11 months

Text

Data Engineers is one of the pioneers in data recovery industry in Delhi India & has been providing a wide range of data recovery services & solutions in delhi.

#Data Engineers #Mobile Data #ssd/flash Media storage Recovery in delhi.#Data Recovery Services #Data Recovery Services in Delhi #Mobile Data Recovery services in delhi

0 notes

techeelashots01 · 1 year

Text

Data Engineering Beginner’s Guide

Here is a starting point for the complicated and ever-evolving discipline of data engineering:

Know the fundamentals of data engineering: Designing and building data pipelines to gather, process, and store huge amounts of data is data engineering. Order to assist data analysis and business intelligence also entails the creation of data models and the use of database technology.

Learn programming languages and tools: Python, SQL, and Java are just a few of the computer languages that are needed for data engineering. It’s also crucial to be familiar with database technologies like SQL Server, MySQL, and MongoDB. Data engineers employ a number of tools, including Apache Kafka, Apache Spark, and Apache Airflow, to create data pipelines.

Study big data technologies: With the amount of data increasing, it’s critical to be knowledgeable about big data technologies like Hadoop, Spark, and NoSQL databases. Data engineers can efficiently handle massive amounts of data thanks to these technologies.

Knowing data governance is important since it entails controlling the security, usability, availability, and accuracy of the data utilized by an organization. To make sure that the data pipeline they create conforms with laws and corporate standards, data engineers should be familiar with data governance policies and procedures.

Develop soft skills: Data engineers must be able to speak clearly with project supervisors, business analysts, and data scientists, among other stakeholders. You’ll excel in this profession if you acquire soft skills like communication, teamwork, and problem-solving.

Keep learning: Data engineering is a discipline that is always changing. Attending conferences, webinars, and training sessions will help you stay current on the newest trends and technologies.

Conclusion

To sum up, data engineering is a challenging field that demands both technical and soft abilities. You may succeed as a data scientist by learning the basic principles of data engineering, picking up languages such as Python and tools, mastering data modeling techniques, picking up on big data technologies, mastering data governance, and honing soft skills.

Source: https://medium.com/@digipyadav/data-engineering-beginners-guide-b7330c56145f

#data engineers #data engineering guide

0 notes

sleepy-bebby · 2 years

Text

Reddit • YouTube

104K notes · View notes

elizabetholevia · 3 days

Text

$2000000 Worth Of Hair Extensions Sold Using This Facebook Ad Set Up

$2000000 Worth Of Hair Extensions Sold Using This Facebook Ad Set Up $2,000,000 Worth Of Hair Extensions Sold Using This Facebook Ad Set Up https://i2.ytimg.com/vi/EHTVOdLS9fA/hqdefault.jpghttps://www.youtube.com/watch?v=EHTVOdLS9fA https://igrowsalons.weebly.com/i-grow-salons/2000000-worth-of-hair-extensions-sold-using-this-facebook-ad-set-up

View On WordPress

#Big Data #Creative Engineer #Data Engineers #Distributed Systems #Software Development #Software Engineering

0 notes

datadiaries · 1 year

Text

Data Engineering Adventures: From ETL Flows to Business Intelligence

Hello, and welcome to my personal blog! My name is Manali Vichare, and I'm currently pursuing a Master of Science in Data Science with a specialization in Business Intelligence at Stevens Institute of Technology. In this blog, I'll be sharing my journey towards becoming a data engineer, my experiences working in the field, and my insights on the latest trends and technologies in data engineering.

As someone with a strong passion for data and analytics, I've been fortunate enough to gain valuable experience in the field of data engineering. My role as a Data Engineer at Digi-Health allowed me to hone my skills in optimizing data warehouse performance and query processing efficiency. I'm particularly proud of the complex ETL flows I've executed and the efficient data migration strategies I've developed using PDI.

But my journey doesn't stop there. My experience as an Ops Data Science intern at Wolters Kluwer in New York City gave me a broader perspective on the role of data in driving business growth and informed decision-making. It was there that I learned the value of using data to support teams and drive success.

Now, as I continue my studies in data science, I'm excited to explore new challenges and opportunities in data engineering and business intelligence. I'm always on the lookout for the latest trends and technologies, and I'm eager to share my insights and experiences with my readers.

As I continue my journey in the field of data analytics and engineering, I hope to inspire others to pursue their passions and seek out opportunities for growth and learning. With the right mindset and determination, anything is possible. Thank you for joining me on this journey, and I look forward to sharing more insights and experiences with you in the future

#dataanalytics #data engineers #datascience

1 note · View note

itsazureops · 1 year

Text

#apechespark #apachespark #datastream #data engineers #confluent #databricks

1 note · View note

xbsoftware · 1 year

Link

How to Overcome Common Challenges in Data Engineering to Make Data Work for You With Minimum Effort

Information is the cornerstone of every business. The way you use the information you have may vary depending on the current needs of your organization. For some, a web app allowing users to check the dates of appointments to the veterinarian will do the trick. Some more demanding business owners may need to use Machine Learning and Artificial Intelligence algorithms to predict customer behavior and adopt their strategy accordingly.

Even if you work in a small company, at some point, you may find that a bunch of excel tables can’t cover your needs anymore. Using different apps that work with different data formats makes everything even more complicated. Without a significant development background, it may be hard even to determine how many databases you need to remain efficient. In such a case, you can rely on data engineers. Their job is to take care of your data infrastructure and the challenges they face along the way will be considered today.

0 notes