#SQL Databases

[futurebird]

Do not help them to build any more of this machine.

If you work with a database and are asked to alter the table structure to comply in advance for citizenship or gender categorizations it's really important to NOT do it.

"The governor is concerned about all this stuff they want us to update our record keeping so we store both gender AND biological sex."

"We need fields to store the country of origin of people's parents."

If you don't have the power to rebuff this yourself, ask for help. At minimum ask for help online anonymously.

Depending on your job you probably have in the past made compromises. Maybe to keep your job. Maybe to survive. This is a bright line. If you are asked to be the one to update the table don't let it be your fingers typing those changes.

If you can't just say "No I won't do that." Stall, run away, feign incompetence. Just don't let it happen.

I suspect this might be where the rubber hits the road first for us around here.

Nothing has changed. You do not have to do it. It is not even ordained.

I know someone who rebuffed such a request. Boss was apologetic "it's what the higher ups want, oh *I* think it's a lot of nonsense, but I don't want us to be out of step ... blah blah"

It was proposed to them in sheepish way. They said it would be a lot of work, not add anything of value, and most important they would not do it. It didn't come up again.

Fascism can be the work of zealots, but there are also many sheepish middle management helping hands who "don't even believe in this really"

There is a lively discussion of this on mastodon. (Mastodon is a very active social network where many people who left twitter have gone over the past few years to escape many problems of big centralized socail media. I like it a lot.) Posting a response to this post over there could be a way to get lots of help and ideas from tech people all over the world with similar values. If you do need help. Please say something.

Also, if you respond to this post I can pass what you say along if that would help too. People will respond and give you ideas to NOT do this should you be asked.

[nixcraft]

Wait what... ? this is dangerous knowledge.

[neuxue]

I need AO3 search to allow window functions

[imall4frogs]

The “genius” of Elon Musk becomes more suspect with each passing day. Hypothetical question: If the source is too stupid to know that his information is wrong, would he be still be spreading disinformation?

[12neonlit-stage]

I go by no pronouns but not as in my name, more so like my pronouns are an undefined variable in shell coding

[mfcl3780cdw]

i have just as much webdev experience as i have IT experience but that world feels so much more alien sometimes.

average reddit post about web development: "yeah to build my website i just use [lists 15 different frameworks and tools that cost hundreds of dollars per license]"

every team i've worked with:

[education43]

What Are the Qualifications for a Data Scientist?

In today's data-driven world, the role of a data scientist has become one of the most coveted career paths. With businesses relying on data for decision-making, understanding customer behavior, and improving products, the demand for skilled professionals who can analyze, interpret, and extract value from data is at an all-time high. If you're wondering what qualifications are needed to become a successful data scientist, how DataCouncil can help you get there, and why a data science course in Pune is a great option, this blog has the answers.

The Key Qualifications for a Data Scientist

To succeed as a data scientist, a mix of technical skills, education, and hands-on experience is essential. Here are the core qualifications required:

1. Educational Background

A strong foundation in mathematics, statistics, or computer science is typically expected. Most data scientists hold at least a bachelor’s degree in one of these fields, with many pursuing higher education such as a master's or a Ph.D. A data science course in Pune with DataCouncil can bridge this gap, offering the academic and practical knowledge required for a strong start in the industry.

2. Proficiency in Programming Languages

Programming is at the heart of data science. You need to be comfortable with languages like Python, R, and SQL, which are widely used for data analysis, machine learning, and database management. A comprehensive data science course in Pune will teach these programming skills from scratch, ensuring you become proficient in coding for data science tasks.

3. Understanding of Machine Learning

Data scientists must have a solid grasp of machine learning techniques and algorithms such as regression, clustering, and decision trees. By enrolling in a DataCouncil course, you'll learn how to implement machine learning models to analyze data and make predictions, an essential qualification for landing a data science job.

4. Data Wrangling Skills

Raw data is often messy and unstructured, and a good data scientist needs to be adept at cleaning and processing data before it can be analyzed. DataCouncil's data science course in Pune includes practical training in tools like Pandas and Numpy for effective data wrangling, helping you develop a strong skill set in this critical area.

5. Statistical Knowledge

Statistical analysis forms the backbone of data science. Knowledge of probability, hypothesis testing, and statistical modeling allows data scientists to draw meaningful insights from data. A structured data science course in Pune offers the theoretical and practical aspects of statistics required to excel.

6. Communication and Data Visualization Skills

Being able to explain your findings in a clear and concise manner is crucial. Data scientists often need to communicate with non-technical stakeholders, making tools like Tableau, Power BI, and Matplotlib essential for creating insightful visualizations. DataCouncil’s data science course in Pune includes modules on data visualization, which can help you present data in a way that’s easy to understand.

7. Domain Knowledge

Apart from technical skills, understanding the industry you work in is a major asset. Whether it’s healthcare, finance, or e-commerce, knowing how data applies within your industry will set you apart from the competition. DataCouncil's data science course in Pune is designed to offer case studies from multiple industries, helping students gain domain-specific insights.

Why Choose DataCouncil for a Data Science Course in Pune?

If you're looking to build a successful career as a data scientist, enrolling in a data science course in Pune with DataCouncil can be your first step toward reaching your goals. Here’s why DataCouncil is the ideal choice:

Comprehensive Curriculum: The course covers everything from the basics of data science to advanced machine learning techniques.

Hands-On Projects: You'll work on real-world projects that mimic the challenges faced by data scientists in various industries.

Experienced Faculty: Learn from industry professionals who have years of experience in data science and analytics.

100% Placement Support: DataCouncil provides job assistance to help you land a data science job in Pune or anywhere else, making it a great investment in your future.

Flexible Learning Options: With both weekday and weekend batches, DataCouncil ensures that you can learn at your own pace without compromising your current commitments.

Conclusion

Becoming a data scientist requires a combination of technical expertise, analytical skills, and industry knowledge. By enrolling in a data science course in Pune with DataCouncil, you can gain all the qualifications you need to thrive in this exciting field. Whether you're a fresher looking to start your career or a professional wanting to upskill, this course will equip you with the knowledge, skills, and practical experience to succeed as a data scientist.

Explore DataCouncil’s offerings today and take the first step toward unlocking a rewarding career in data science! Looking for the best data science course in Pune? DataCouncil offers comprehensive data science classes in Pune, designed to equip you with the skills to excel in this booming field. Our data science course in Pune covers everything from data analysis to machine learning, with competitive data science course fees in Pune. We provide job-oriented programs, making us the best institute for data science in Pune with placement support. Explore online data science training in Pune and take your career to new heights!

[demo-ness]

my old advisor was """restructured""" a while ago and my new one can be SO frustrating. they spent several emails working on the assumption that i had veteran benefits, for some reason, and in our most recent interaction they just full on ignored my question about whether a class i wanted to take would be viable or not. WHAT DO YOU THINK WE'RE HERE TO DO, MAN

[scvnthorpe]

That time I restored a Database view

Recently at work we've been migrating an old database system to a new platform to save money - this kind of shit is what makes your business processes faster, cheaper and more correct - and this has entailed sifting through a lot of tables, views, and views made of tables and views!

As it happens the finance guy who does all the payroll and expenses is a great guy to work with and basically the one person who knows all the relevant business rules, but also basically treats databases like they're excel workbooks. As such you have a bunch of bits stitched to each other and we're just figuring out how to first move everything and then ease into a well-oiled relational model with no duplication and all together on a single database.

While we in the dev team were figuring out how to do this for finance we were recently testing out a modified version of a view built on top of the old version and accidentally deleted the old version and not the modified testing version.

Mistakes are bound to happen, but we needed to figure out how to either restore it or at least figure out how to work without it because finance people love their data views and reports. There are probably clever things you can do with any DBMS to find shit you just dropped and restore it from backup, but I then realised that I'd been tasked with generating all the scripts for the database objects. There had to be a script laying around!

Sure enough I went to dig up the build script for the dropped view, and I ran it.

I queried it, and everything was back in place.

Shit goes wrong sometimes, but having the right failsafes can really make a difference.

Script your shit, use backups, use version control!

[uthra-krish]

The Skills I Acquired on My Path to Becoming a Data Scientist

Data science has emerged as one of the most sought-after fields in recent years, and my journey into this exciting discipline has been nothing short of transformative. As someone with a deep curiosity for extracting insights from data, I was naturally drawn to the world of data science. In this blog post, I will share the skills I acquired on my path to becoming a data scientist, highlighting the importance of a diverse skill set in this field.

The Foundation — Mathematics and Statistics

At the core of data science lies a strong foundation in mathematics and statistics. Concepts such as probability, linear algebra, and statistical inference form the building blocks of data analysis and modeling. Understanding these principles is crucial for making informed decisions and drawing meaningful conclusions from data. Throughout my learning journey, I immersed myself in these mathematical concepts, applying them to real-world problems and honing my analytical skills.

Programming Proficiency

Proficiency in programming languages like Python or R is indispensable for a data scientist. These languages provide the tools and frameworks necessary for data manipulation, analysis, and modeling. I embarked on a journey to learn these languages, starting with the basics and gradually advancing to more complex concepts. Writing efficient and elegant code became second nature to me, enabling me to tackle large datasets and build sophisticated models.

Data Handling and Preprocessing

Working with real-world data is often messy and requires careful handling and preprocessing. This involves techniques such as data cleaning, transformation, and feature engineering. I gained valuable experience in navigating the intricacies of data preprocessing, learning how to deal with missing values, outliers, and inconsistent data formats. These skills allowed me to extract valuable insights from raw data and lay the groundwork for subsequent analysis.

Data Visualization and Communication

Data visualization plays a pivotal role in conveying insights to stakeholders and decision-makers. I realized the power of effective visualizations in telling compelling stories and making complex information accessible. I explored various tools and libraries, such as Matplotlib and Tableau, to create visually appealing and informative visualizations. Sharing these visualizations with others enhanced my ability to communicate data-driven insights effectively.

Machine Learning and Predictive Modeling

Machine learning is a cornerstone of data science, enabling us to build predictive models and make data-driven predictions. I delved into the realm of supervised and unsupervised learning, exploring algorithms such as linear regression, decision trees, and clustering techniques. Through hands-on projects, I gained practical experience in building models, fine-tuning their parameters, and evaluating their performance.

Database Management and SQL

Data science often involves working with large datasets stored in databases. Understanding database management and SQL (Structured Query Language) is essential for extracting valuable information from these repositories. I embarked on a journey to learn SQL, mastering the art of querying databases, joining tables, and aggregating data. These skills allowed me to harness the power of databases and efficiently retrieve the data required for analysis.

Domain Knowledge and Specialization

While technical skills are crucial, domain knowledge adds a unique dimension to data science projects. By specializing in specific industries or domains, data scientists can better understand the context and nuances of the problems they are solving. I explored various domains and acquired specialized knowledge, whether it be healthcare, finance, or marketing. This expertise complemented my technical skills, enabling me to provide insights that were not only data-driven but also tailored to the specific industry.

Soft Skills — Communication and Problem-Solving

In addition to technical skills, soft skills play a vital role in the success of a data scientist. Effective communication allows us to articulate complex ideas and findings to non-technical stakeholders, bridging the gap between data science and business. Problem-solving skills help us navigate challenges and find innovative solutions in a rapidly evolving field. Throughout my journey, I honed these skills, collaborating with teams, presenting findings, and adapting my approach to different audiences.

Continuous Learning and Adaptation

Data science is a field that is constantly evolving, with new tools, technologies, and trends emerging regularly. To stay at the forefront of this ever-changing landscape, continuous learning is essential. I dedicated myself to staying updated by following industry blogs, attending conferences, and participating in courses. This commitment to lifelong learning allowed me to adapt to new challenges, acquire new skills, and remain competitive in the field.

In conclusion, the journey to becoming a data scientist is an exciting and dynamic one, requiring a diverse set of skills. From mathematics and programming to data handling and communication, each skill plays a crucial role in unlocking the potential of data. Aspiring data scientists should embrace this multidimensional nature of the field and embark on their own learning journey. If you want to learn more about Data science, I highly recommend that you contact ACTE Technologies because they offer Data Science courses and job placement opportunities. Experienced teachers can help you learn better. You can find these services both online and offline. Take things step by step and consider enrolling in a course if you’re interested. By acquiring these skills and continuously adapting to new developments, they can make a meaningful impact in the world of data science.

[pancakeke]

I made a big report a year ago that compares what components were allocated to orders the previous week vs what are allocated now (accounting for consumption n such). it looks at 100% of inventory in 100% of locations. for the first 9 months I was just logging changes while no one gave a shit cause everyone blew off our weekly inventory meeting so there was no one to review anything. but no one can do that anymore :)

I have all the part numbers, quantities, dollar values, and customer accounts laid out very nicely so no one in sales can accuse supply chain of buying stuff for no reason when really they changed their orders around without telling anyone so they wouldn't have to admit making any mistakes.

this report hasn't made them stop trying to lie/hide things in the first place tho. maybe one day.

[fortunatelycoldengineer]

SQL Interview Question . . . For more interview questions https://bit.ly/3RLDWt9 check the above link

[amparol12]

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[harryfebus]

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[madesimplemssql]

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