#csvkit
Explore tagged Tumblr posts
Visit Tumblr Blog
Explore Tumblr blogs with no restrictions, modern design and the best experience.
Last Seen Tumblr Blogs
Fun Fact
The total number of visits Tumblr.com received during January 2021 is 327 million.
Link
A quick repo with basic command line commands, plus a very brief CSVKit run through.
3 notes
·
View notes
Text
project tools
No project is ever complete until you have all the tools you need to finish it. Whether you're working on a home renovation or a big business project, having the right tools makes the job much easier and faster. We've put together a list of project tools that are perfect for various types of projects.
The following tools can be used to help with various aspects of a project:
-GIMP: A free and open source image editor that can be used to edit photos, graphics, and logos.
-Wordpress: A popular website builder that can be used to create a website from scratch or to improve an existing website.
-CMS: A content management system that allows users to manage and publish content online.
- SEO: Search engine optimization techniques that can be used to improve the visibility of a website or blog.
project tools
There are so many tools available for project managers, it can be hard to know where to start. Luckily, we've compiled a list of our favorite tools for managing projects. Whether you're looking for a comprehensive project management software, a spreadsheet for tracking deadlines, or a dedicated task tracker, we've got you covered.
1. Asana: Asana is one of the most popular project management tools on the market, and for good reason. It's comprehensive, user-friendly, and has an impressive range of features. Some of our favorites include its task management and deadline tracking features.
2. Trello: Trello is another great tool for managing projects. It's easy to use and comes with a range of features to help you track your progress. Our favorites include its drag-and-drop interface and its ability to keep track of multiple teams working on a project simultaneously.
3. CSVKit: CSVKit is perfect if you need to manage large amounts of data related to your projects. It has an impressive range of features to help you organize your data and keep track of your progress.
4. Google Sheets: Google Sheets is a great way to organize your data and keep
If you're just getting started with projects, your first stop should be the Project Tools blog. This blog is written by Project Manager and Developer Tim Brown, and it's a great place to start if you're new to project management or development.
In this blog post, Tim explains how to create a simple project plan. He starts by explaining the different types of project plans and how they can help you organize your work. Then he shows you how to create a simple project plan in Microsoft Project.
If you're more advanced, the Project Tools blog has plenty of information for you too. In this post, Tim explains how to use milestones and Milestones Groups in Microsoft Project. He also shows you how to use task sequences and work packages in Microsoft Project.
Finally, in this post, Tim explains how to use resource planning tools in Microsoft Project. He covers scheduling tools like Availability Zones and Real-Time Scheduling, as well as resource planning tools like Resource Pools and Cost Elements.
So whether you're starting out with projects or are looking for tips on using more advanced features of Microsoft Project, be sure to check out the Project Tools blog section!
0 notes
Text
Why should you take the PG Diploma in Data Science using Python?
Believe it or not, the fastest-growing Python usage is for data science. Behind the massive fan following of the Python lies numerous conditions. Python is a very simple language to learn. While on the other hand, Data Science using Python is a nifty tool with a range of benefits. As it is open-source, Python's flexibility and continuous improvements with Data Science have become a genuinely resourceful option.
Other integrated languages, such as Java, can be utilized in this well-established system. It is extremely beneficial for your professional to pursue data science training and have a bright future full of possibilities. It is crucial to get in touch with the best data science training institute in Bangalore for ideal support from the industry trainer in every possible way. Cranes Varsity is the top data science using python training institute where you'll not only learn but explore and build a future that will take you high in life with promising job placements.
Why is Python for Data Science the best?
Data science using python is in high demand across the globe. There are a few grounds to support the statement that Data Science with Python is the best among all to choose as a great career option. There are notable advantages to learning this, which are all listed below;
1: Simplistic Approach :
Python is very popular as a programming language mainly due to its simplicity. The best features are inherited with easy readability, making it a friendly language for beginners or freshers. It is time savvy which allows straightaway to get into the research part without spending most of its time in documentation. It is extensively used in statistical analysis, text processing, data analysis, web development, and much more.
2: One library for every sort of need:
In Data Science using Python, the following is the most assorted library that makes it propelling to Data Science professionals. Python libraries include;
● NumPy is one of the most accessible libraries to find the use case in Data science.
● Pandas are built on the top of the NumPy.
● SciPy is the scientific equivalent of NumPy.
There are some more libraries like SymPy (statistical applications); Shogun, PyLearn2, and PyMC (machine learning); Bokeh, ggplot, Plotly, prettyplotlib, and seaborn (data visualization and plotting), and csvkit, PyTables, SQLite3 (data formatting and storage), to name a few.
3: It’s Multi-paradigm Approach
A great thing about Python is it's not limited to any programming language. The multi-paradigm feature makes it unique, which enables the support of functional, procedural, and objective-oriented programming & aspect-oriented programming style as well. With the data science certification, all this knowledge you'll gain eventually in training.
Who are all eligible for the data science online course?
Once you know about the immense benefits that you'll gather with the learning of Python in Data Science, you must be feeling to find out who is eligible for this? At Cranes Varsity, you can apply for the Data Science using Python training course if you are a working professional from an Engineering background, who is willing to increase your knowledge for better career aspects.
What is included in the data science training?
At Cranes Varsity, Data Science using Python training course syllabus is well-structured in terms of modules that will help the students better understand the subject. It includes:
● Relational Database - MySQL
● NoSQL - Mongo DB
● Web Technology - HTML, CSS, JavaScript
● Python Programming
● Advanced Python & Unit Testing
● Statistics
● Data Analysis & Visualization
● Machine Learning using SKlearn
● Deep Learning using Tenser Flow
● Tableau, Cloud Computing
You'll learn:
● Understand concepts like lambdas and CSV file manipulation.
● Describe standard Python data science functionality and features.
● For cleaning and processing, use DataFrame structures.
● Explain how t-tests, sampling, and distributions work.
About the PG Diploma in Data Science with Python at Cranes Varsity
The PG Diploma in Data Science using Python is a four-month professional program that provides solid knowledge and comprehension of Data Science. The expert teachers/ trainers have been industry leaders for decades. They offer instruction in all necessary disciplines so that engineers may create Java-based applications that satisfy industry standards.
As the best data science training institute in Bangalore, Cranes provides students with an organized framework to help them improve their technical skills and knowledge curve. The lectures are well-planned and delivered using examples to make them more engaging and understandable. The goal is to help students develop more strong knowledge representations in their heads in Data Science using Python.
Choosing Crane s Varsity is ideal for you in many ways:
● Extraordinary faculty who are practically experienced for years and know in and out of the market trends.
● Online and offline assistance from time to time.
● All notes are provided related to the Data Science using Python
● Guaranteed placement to the top companies in the country
● Extensive study and knowledge sharing sessions
● Open discussions are appreciated
● Full-time assistance 24/7 over time
● Timely assessment
How valuable is the data science certification?
Once you have chosen the data science online course from Cranes Varsity, there is no looking back. Your qualifications will be valued at the best ways to the top class management where you can explore more opportunities. The chances of placement are guaranteed from the Cranes campus for those who complete the training successfully. Data Science using Python training course is not just a course. It is a promising way to advance with the trend and demands of employment opportunities for the long run.
The platforms used in the Cranes Varsity for offering Data Science Using Python are;
● Anaconda Distribution (Jupyter Notebook)
● Tableau
● MYSQL
● Mongo DB
● Google Colab
● AWS
Any data science using python training institute won't offer such versatility in the module designing and syllabus that covers so much, apart from Cranes Varsity. The placement opportunities are on a larger scale to the top organizations in the country. Do not wait and skip your chance; apply/register for the course today! With this helpful data science using python certification, you'll surely see a better career for yourself.
0 notes
Link
Keep those hands on the keyboard! We can do a lot on OSX and Linux without touching a mouse or GUI. Awesome command line tools for NX derivatives have been around since day one, and have expanded to include Python, Go, NodeJS, and hybrid tools. Even if you are not only running your pipeline through the command line, you can call most of these tools from Apache NiFi for processing.
The book Data Science at the Command Line and GitHub offer an amazing set of quality tools to do a lot of pre- and post-processing and allow for a lot of transformations. I highly recommend looking at all of these amazing tools.
CSVKit is amazing! It does everything you need with comma-separated values. You can grab columns via cvs cut, filter by column with cvsgrip, extract data from Postgresql to CSV via sql2csv, grab a subset of columns with cols , and convert MS Excel to CSV with in2cv.
Quick Tool List
Python Data Analysis (Agate).
ImageMagick (edit, create, convert, flip, and alter images from the command-line).
JSON 2 CSV.
XML2JSON via NodeJS.
HTML to image.
HTML to PDF.
Weather Underground CLI.
NIFI Shell.
Gatling for Testing with Scala/JVM.
Kafka Producer with JSON.
Kafka Consumer with JSON.
Create JSON.
Image MetaData Extraction.
OSQuery for Querying Infrastructure.
Tesseract for Command Line OCR.
Hadoop/HDFS Command Line Tools
CURL.
WGET.
MQTT CLI (NPM.JS).
8 notes
·
View notes
Text
0 notes
Text
Data Wrangling Market Size, Share, Industry Analysis & Forecast to 2025
The global data wrangling market is significantly influenced by the widespread adoption of data wrangling tools for performing edge analytics. The growing adoption of AI, edge computing, increasing volume and velocity of data, advancement in the IoT along with increasing regulatory reforms are the major factors that are driving the growth of the global data wrangling industry. Besides, growing smart cities projects across the globe is one of the other major factors contributing to the growth of the market. Rapidly growing data volume across the various industrial verticals is generating demand for advanced analytics algorithms by enterprises to take insights from a significant amount of generated data.
Request a free sample of our report on Data Wrangling Market: https://www.omrglobal.com/request-sample/data-wrangling-market
Due to a large scale adoption edge analytics, data wrangling tools are extensively used by verticals such as automotive, BFSI, retail and e-commerce, and many others. Businesses are adopting analytical solutions for recognition of the data pattern, identification of the issues related to the inconsistent data, and to analyze the data. This tool enables the enterprises to have more comprehensive control over their system. Data wrangling procedure allows an enterprise to filter out unwanted data and transform it into structured data to be used by AI and ML algorithms for analyzing and providing data insights. This procedure enlarges the data usage in the organization and enriches the potential value of data to the business. North America is expected to dominate the global data wrangling market owing to the rising adoption of data wrangling tools and services. In North America, Canada is expected to provide significant growth to the market. In North America, an increasing volume of data that is collected every day has increased the demand for data wrangling tools and services. Besides, the presence of developed economies in the region is another factor that is driving the growth of this market. Moreover, the growth of the market in the region is attributed to the presence of major players such as IBM, Hitachi Vantra, Oracle, and Trifacta.
Visit here to know more about Global Data Wrangling Market size.
Moreover, the global data wrangling market growth is accelerated by market activities such as mergers & acquisitions, collaboration & partnerships that are adopted by the major companies of the market. IBM, Oracle, SAS Institute, Dataiku, Trifacta, DataWatch Corp., and others are the major manufacturers of the market. IBM, an IT pioneer has the strategy of launching new products for meeting the demand for structured information for enterprises. The company has entered into several strategic agreements and partnerships for making improvements in its product and service offerings to increase its customer base. For instance, in May 2018, IBM has acquired Armanta, INC., a software firm that provides analytics software for financial services firms to get insight into the financial sector.
Current Market Trends Covered in the market report:
Previously Excel and SQL were used for the data wrangling purpose.
In present times CSVKit, DataWrangler, Mr. Data Converter, Openrefine, Python and Pandas, and Trifacta wrangler are used for data wrangling
Partnerships & collaborations and new product launch- key drivers of competition in this market.
Asia-Pacific to Emerge as a Fastest-Growing Data Wrangling Market.
Increasing regulatory pressure and growth in edge computing- a significant opportunity for market players.
Data Wrangling Market Segmentation
By Deployment Type
On-Premises
Cloud-Based
By End-Use
BFSI
Consumer & Retail industry
IT & Telecommunication
Healthcare
Others
Data Wrangling Market – Segment by Region
North America
Europe
Asia-Pacific
Rest of the World
A full report of Global Data Wrangling Market is available at: https://www.omrglobal.com/industry-reports/data-wrangling-market
About Orion Market Research
Orion Market Research (OMR) is an Indian market research and consulting company known for its crisp and concise reports. The company is equipped with an experienced team of analysts and consultants. OMR offers quality syndicated research reports, customized research reports, consulting and other research-based services.
Media Contact:
Company Name: Orion Market Reports
Contact Person: Mr. Anurag Tiwari
Email: [email protected]
Contact no: +1 646-755-7667, +91 780-304-0404
0 notes
Text
The state (or statelessness) of technical SEO in 2019
What do we need to know about technical SEO in 2019? Here’s an overview to keep in mind.
Technical SEO is different from what we know as standard SEO. It dives deeper into the analysis of content and it can help you draw very interesting conclusions.
Mike King from iPullRank delivered a highly informative presentation in Catalyst’s TechSEO Boost and it can give us a better idea of the state, or actually, the statelessness of technical SEO.
Whether you’re an SEO expert or you’re just getting started, here are some key points to consider from Mike’s session.
Defining technical SEO
The first challenge that comes with technical SEO has to do with its actual definition. It’s not always easy to explain it.
In fact, it’s even hard for SEO professionals to define it.
Mike King asked 300 people to provide their own definition to what technical SEO really is. Unsurprisingly, there was no consistency in its definition. Many respondents indicated that web performance and information architecture are parts of what technical SEO does. However, these are tasks that other roles typically perform.
As Mike King said, “everything we do is someone else’s job.”
The best way to define technical SEO as a profession then is to think of it as the state of being curious. Technical SEO experts are curious enough to play with things that they can change.
What we need to remember is that there is no technical SEO as a definitive discipline. It can be the job of putting things together to make things scale and solve problems that affect SEO.
Thus, if we want to explain the difference between technical and standard SEO, we need to remember that technical SEO is about scalability, depth, detail, advanced cross-functional understanding, and also execution.
The challenge of metrics
Another challenge that we’re seeing in technical SEO — and SEO in general sometimes — is that the metrics are too opaque.
There are many tools to measure our own definition of success but we still don’t have peer-reviewed and transparent definitions of any proprietary link metrics.
How can we tell which metrics matter most of all? How do we define success and how can we all agree to it?
These bring out the need to standardize SEO.
We need to standardize three things:
Open PageRank Computation
Crawl Data Portability
Open Rankings
These can help us improve our SEO expertise by sharing a common understanding with everyone in the industry.
Technical SEO in 2019
If you want to improve your technical SEO skills in 2019, here are some key things to consider.
Natural language generation can be a great ally in the future. We can take care of the good content and it can perfectly optimize it for the SERPs.
Semantic keyword research can also be helpful and it’s important to spend more time on it. It can even help you pull the right SEO metrics to draw better conclusions.
There are three types of tests that are most relevant to technical SEO:
Unit tests (testing an individual function to ensure that it works)
Integration tests (using your logic to build a bigger system)
UI tests (testing frontend interface on your website, which is the slowest version of testing)
Headless browsers can be very useful in the process of test-driven development. We tend to use them for Javascript-rendered content but they are actually made for automated testing.
From this perspective, we can think of technical SEO professionals as product managers. They are focusing on a test-driven development to run tests and experiment with different scenarios.
Here are some additional tips that have to do with technical SEO:
There will always be technical expectations for content that ranks well. We can deal these with the right text analysis, the perfect optimization and the content review that will lead to exactly what Google wants to see.
It’s useful to spend more time on automated testing, unit testing and also headless browsers. You can perform tests to see if they are how you expect them to be. It’s the idea of test-driven development that can help you check every single component.
Log file analysis is crucial. If you’re not doing it, then you’re just guessing.
PageRank is still our measurement. Even if we don’t have complete visibility, it’s still important to understand it.
We need to be proactive to understand Google. Don’t be afraid to dig into data to understand how Google works
Don’t underestimate the power of internal link building. The larger the page, the higher the success.
Tools to use in technical SEO
If you want to start using the right tools for technical SEO, here is the list that Mike provided in his presentation.
Ryte
Botify
Cognitive SEO
Chrome canary
Csvkit
Knime
MonkeyLearn
You can also find out more about free technical SEO tools in our own list.
Overview
What we need to remember when it comes to technical SEO is that it’s all about being curious. You don’t need to have a clear definition of your role and your tasks. These may depend on the company that you’re working for.
But you still need to be comfortable with figuring out how things work. You need to have the inquisitive mind to investigate why one thing succeeded over another.
And this is probably the best way to dive into it with the right mindset.
The post The state (or statelessness) of technical SEO in 2019 appeared first on Search Engine Watch.
source https://searchenginewatch.com/2019/02/06/technical-seo-2019-statelessness/ from Rising Phoenix SEO http://risingphoenixseo.blogspot.com/2019/02/the-state-or-statelessness-of-technical.html
0 notes
Text
The state (or statelessness) of technical SEO in 2019
What do we need to know about technical SEO in 2019? Here’s an overview to keep in mind.
Technical SEO is different from what we know as standard SEO. It dives deeper into the analysis of content and it can help you draw very interesting conclusions.
Mike King from iPullRank delivered a highly informative presentation in Catalyst’s TechSEO Boost and it can give us a better idea of the state, or actually, the statelessness of technical SEO.
Whether you’re an SEO expert or you’re just getting started, here are some key points to consider from Mike’s session.
Defining technical SEO
The first challenge that comes with technical SEO has to do with its actual definition. It’s not always easy to explain it.
In fact, it’s even hard for SEO professionals to define it.
Mike King asked 300 people to provide their own definition to what technical SEO really is. Unsurprisingly, there was no consistency in its definition. Many respondents indicated that web performance and information architecture are parts of what technical SEO does. However, these are tasks that other roles typically perform.
As Mike King said, “everything we do is someone else’s job.”
The best way to define technical SEO as a profession then is to think of it as the state of being curious. Technical SEO experts are curious enough to play with things that they can change.
What we need to remember is that there is no technical SEO as a definitive discipline. It can be the job of putting things together to make things scale and solve problems that affect SEO.
Thus, if we want to explain the difference between technical and standard SEO, we need to remember that technical SEO is about scalability, depth, detail, advanced cross-functional understanding, and also execution.
The challenge of metrics
Another challenge that we’re seeing in technical SEO — and SEO in general sometimes — is that the metrics are too opaque.
There are many tools to measure our own definition of success but we still don’t have peer-reviewed and transparent definitions of any proprietary link metrics.
How can we tell which metrics matter most of all? How do we define success and how can we all agree to it?
These bring out the need to standardize SEO.
We need to standardize three things:
Open PageRank Computation
Crawl Data Portability
Open Rankings
These can help us improve our SEO expertise by sharing a common understanding with everyone in the industry.
Technical SEO in 2019
If you want to improve your technical SEO skills in 2019, here are some key things to consider.
Natural language generation can be a great ally in the future. We can take care of the good content and it can perfectly optimize it for the SERPs.
Semantic keyword research can also be helpful and it’s important to spend more time on it. It can even help you pull the right SEO metrics to draw better conclusions.
There are three types of tests that are most relevant to technical SEO:
Unit tests (testing an individual function to ensure that it works)
Integration tests (using your logic to build a bigger system)
UI tests (testing frontend interface on your website, which is the slowest version of testing)
Headless browsers can be very useful in the process of test-driven development. We tend to use them for Javascript-rendered content but they are actually made for automated testing.
From this perspective, we can think of technical SEO professionals as product managers. They are focusing on a test-driven development to run tests and experiment with different scenarios.
Here are some additional tips that have to do with technical SEO:
There will always be technical expectations for content that ranks well. We can deal these with the right text analysis, the perfect optimization and the content review that will lead to exactly what Google wants to see.
It’s useful to spend more time on automated testing, unit testing and also headless browsers. You can perform tests to see if they are how you expect them to be. It’s the idea of test-driven development that can help you check every single component.
Log file analysis is crucial. If you’re not doing it, then you’re just guessing.
PageRank is still our measurement. Even if we don’t have complete visibility, it’s still important to understand it.
We need to be proactive to understand Google. Don’t be afraid to dig into data to understand how Google works
Don’t underestimate the power of internal link building. The larger the page, the higher the success.
Tools to use in technical SEO
If you want to start using the right tools for technical SEO, here is the list that Mike provided in his presentation.
Ryte
Botify
Cognitive SEO
Chrome canary
Csvkit
Knime
MonkeyLearn
You can also find out more about free technical SEO tools in our own list.
Overview
What we need to remember when it comes to technical SEO is that it’s all about being curious. You don’t need to have a clear definition of your role and your tasks. These may depend on the company that you’re working for.
But you still need to be comfortable with figuring out how things work. You need to have the inquisitive mind to investigate why one thing succeeded over another.
And this is probably the best way to dive into it with the right mindset.
The post The state (or statelessness) of technical SEO in 2019 appeared first on Search Engine Watch.
from IM Tips And Tricks https://searchenginewatch.com/2019/02/06/technical-seo-2019-statelessness/ from Rising Phoenix SEO https://risingphxseo.tumblr.com/post/182606004540
0 notes
Text
The state (or statelessness) of technical SEO in 2019
What do we need to know about technical SEO in 2019? Here’s an overview to keep in mind.
Technical SEO is different from what we know as standard SEO. It dives deeper into the analysis of content and it can help you draw very interesting conclusions.
Mike King from iPullRank delivered a highly informative presentation in Catalyst’s TechSEO Boost and it can give us a better idea of the state, or actually, the statelessness of technical SEO.
Whether you’re an SEO expert or you’re just getting started, here are some key points to consider from Mike’s session.
Defining technical SEO
The first challenge that comes with technical SEO has to do with its actual definition. It’s not always easy to explain it.
In fact, it’s even hard for SEO professionals to define it.
Mike King asked 300 people to provide their own definition to what technical SEO really is. Unsurprisingly, there was no consistency in its definition. Many respondents indicated that web performance and information architecture are parts of what technical SEO does. However, these are tasks that other roles typically perform.
As Mike King said, “everything we do is someone else’s job.”
The best way to define technical SEO as a profession then is to think of it as the state of being curious. Technical SEO experts are curious enough to play with things that they can change.
What we need to remember is that there is no technical SEO as a definitive discipline. It can be the job of putting things together to make things scale and solve problems that affect SEO.
Thus, if we want to explain the difference between technical and standard SEO, we need to remember that technical SEO is about scalability, depth, detail, advanced cross-functional understanding, and also execution.
The challenge of metrics
Another challenge that we’re seeing in technical SEO — and SEO in general sometimes — is that the metrics are too opaque.
There are many tools to measure our own definition of success but we still don’t have peer-reviewed and transparent definitions of any proprietary link metrics.
How can we tell which metrics matter most of all? How do we define success and how can we all agree to it?
These bring out the need to standardize SEO.
We need to standardize three things:
Open PageRank Computation
Crawl Data Portability
Open Rankings
These can help us improve our SEO expertise by sharing a common understanding with everyone in the industry.
Technical SEO in 2019
If you want to improve your technical SEO skills in 2019, here are some key things to consider.
Natural language generation can be a great ally in the future. We can take care of the good content and it can perfectly optimize it for the SERPs.
Semantic keyword research can also be helpful and it’s important to spend more time on it. It can even help you pull the right SEO metrics to draw better conclusions.
There are three types of tests that are most relevant to technical SEO:
Unit tests (testing an individual function to ensure that it works)
Integration tests (using your logic to build a bigger system)
UI tests (testing frontend interface on your website, which is the slowest version of testing)
Headless browsers can be very useful in the process of test-driven development. We tend to use them for Javascript-rendered content but they are actually made for automated testing.
From this perspective, we can think of technical SEO professionals as product managers. They are focusing on a test-driven development to run tests and experiment with different scenarios.
Here are some additional tips that have to do with technical SEO:
There will always be technical expectations for content that ranks well. We can deal these with the right text analysis, the perfect optimization and the content review that will lead to exactly what Google wants to see.
It’s useful to spend more time on automated testing, unit testing and also headless browsers. You can perform tests to see if they are how you expect them to be. It’s the idea of test-driven development that can help you check every single component.
Log file analysis is crucial. If you’re not doing it, then you’re just guessing.
PageRank is still our measurement. Even if we don’t have complete visibility, it’s still important to understand it.
We need to be proactive to understand Google. Don’t be afraid to dig into data to understand how Google works
Don’t underestimate the power of internal link building. The larger the page, the higher the success.
Tools to use in technical SEO
If you want to start using the right tools for technical SEO, here is the list that Mike provided in his presentation.
Ryte
Botify
Cognitive SEO
Chrome canary
Csvkit
Knime
MonkeyLearn
You can also find out more about free technical SEO tools in our own list.
Overview
What we need to remember when it comes to technical SEO is that it’s all about being curious. You don’t need to have a clear definition of your role and your tasks. These may depend on the company that you’re working for.
But you still need to be comfortable with figuring out how things work. You need to have the inquisitive mind to investigate why one thing succeeded over another.
And this is probably the best way to dive into it with the right mindset.
The post The state (or statelessness) of technical SEO in 2019 appeared first on Search Engine Watch.
from Digtal Marketing News https://searchenginewatch.com/2019/02/06/technical-seo-2019-statelessness/
0 notes
Text
The state (or statelessness) of technical SEO in 2019
What do we need to know about technical SEO in 2019? Here’s an overview to keep in mind.
Technical SEO is different from what we know as standard SEO. It dives deeper into the analysis of content and it can help you draw very interesting conclusions.
Mike King from iPullRank delivered a highly informative presentation in Catalyst’s TechSEO Boost and it can give us a better idea of the state, or actually, the statelessness of technical SEO.
Whether you’re an SEO expert or you’re just getting started, here are some key points to consider from Mike’s session.
Defining technical SEO
The first challenge that comes with technical SEO has to do with its actual definition. It’s not always easy to explain it.
In fact, it’s even hard for SEO professionals to define it.
Mike King asked 300 people to provide their own definition to what technical SEO really is. Unsurprisingly, there was no consistency in its definition. Many respondents indicated that web performance and information architecture are parts of what technical SEO does. However, these are tasks that other roles typically perform.
As Mike King said, “everything we do is someone else’s job.”
The best way to define technical SEO as a profession then is to think of it as the state of being curious. Technical SEO experts are curious enough to play with things that they can change.
What we need to remember is that there is no technical SEO as a definitive discipline. It can be the job of putting things together to make things scale and solve problems that affect SEO.
Thus, if we want to explain the difference between technical and standard SEO, we need to remember that technical SEO is about scalability, depth, detail, advanced cross-functional understanding, and also execution.
The challenge of metrics
Another challenge that we’re seeing in technical SEO — and SEO in general sometimes — is that the metrics are too opaque.
There are many tools to measure our own definition of success but we still don’t have peer-reviewed and transparent definitions of any proprietary link metrics.
How can we tell which metrics matter most of all? How do we define success and how can we all agree to it?
These bring out the need to standardize SEO.
We need to standardize three things:
Open PageRank Computation
Crawl Data Portability
Open Rankings
These can help us improve our SEO expertise by sharing a common understanding with everyone in the industry.
Technical SEO in 2019
If you want to improve your technical SEO skills in 2019, here are some key things to consider.
Natural language generation can be a great ally in the future. We can take care of the good content and it can perfectly optimize it for the SERPs.
Semantic keyword research can also be helpful and it’s important to spend more time on it. It can even help you pull the right SEO metrics to draw better conclusions.
There are three types of tests that are most relevant to technical SEO:
Unit tests (testing an individual function to ensure that it works)
Integration tests (using your logic to build a bigger system)
UI tests (testing frontend interface on your website, which is the slowest version of testing)
Headless browsers can be very useful in the process of test-driven development. We tend to use them for Javascript-rendered content but they are actually made for automated testing.
From this perspective, we can think of technical SEO professionals as product managers. They are focusing on a test-driven development to run tests and experiment with different scenarios.
Here are some additional tips that have to do with technical SEO:
There will always be technical expectations for content that ranks well. We can deal these with the right text analysis, the perfect optimization and the content review that will lead to exactly what Google wants to see.
It’s useful to spend more time on automated testing, unit testing and also headless browsers. You can perform tests to see if they are how you expect them to be. It’s the idea of test-driven development that can help you check every single component.
Log file analysis is crucial. If you’re not doing it, then you’re just guessing.
PageRank is still our measurement. Even if we don’t have complete visibility, it’s still important to understand it.
We need to be proactive to understand Google. Don’t be afraid to dig into data to understand how Google works
Don’t underestimate the power of internal link building. The larger the page, the higher the success.
Tools to use in technical SEO
If you want to start using the right tools for technical SEO, here is the list that Mike provided in his presentation.
Ryte
Botify
Cognitive SEO
Chrome canary
Csvkit
Knime
MonkeyLearn
You can also find out more about free technical SEO tools in our own list.
Overview
What we need to remember when it comes to technical SEO is that it’s all about being curious. You don’t need to have a clear definition of your role and your tasks. These may depend on the company that you’re working for.
But you still need to be comfortable with figuring out how things work. You need to have the inquisitive mind to investigate why one thing succeeded over another.
And this is probably the best way to dive into it with the right mindset.
The post The state (or statelessness) of technical SEO in 2019 appeared first on Search Engine Watch.
from Digtal Marketing News https://searchenginewatch.com/2019/02/06/technical-seo-2019-statelessness/
0 notes
Text
The state (or statelessness) of technical SEO in 2019
What do we need to know about technical SEO in 2019? Here’s an overview to keep in mind.
Technical SEO is different from what we know as standard SEO. It dives deeper into the analysis of content and it can help you draw very interesting conclusions.
Mike King from iPullRank delivered a highly informative presentation in Catalyst’s TechSEO Boost and it can give us a better idea of the state, or actually, the statelessness of technical SEO.
Whether you’re an SEO expert or you’re just getting started, here are some key points to consider from Mike’s session.
Defining technical SEO
The first challenge that comes with technical SEO has to do with its actual definition. It’s not always easy to explain it.
In fact, it’s even hard for SEO professionals to define it.
Mike King asked 300 people to provide their own definition to what technical SEO really is. Unsurprisingly, there was no consistency in its definition. Many respondents indicated that web performance and information architecture are parts of what technical SEO does. However, these are tasks that other roles typically perform.
As Mike King said, “everything we do is someone else’s job.”
The best way to define technical SEO as a profession then is to think of it as the state of being curious. Technical SEO experts are curious enough to play with things that they can change.
What we need to remember is that there is no technical SEO as a definitive discipline. It can be the job of putting things together to make things scale and solve problems that affect SEO.
Thus, if we want to explain the difference between technical and standard SEO, we need to remember that technical SEO is about scalability, depth, detail, advanced cross-functional understanding, and also execution.
The challenge of metrics
Another challenge that we’re seeing in technical SEO — and SEO in general sometimes — is that the metrics are too opaque.
There are many tools to measure our own definition of success but we still don’t have peer-reviewed and transparent definitions of any proprietary link metrics.
How can we tell which metrics matter most of all? How do we define success and how can we all agree to it?
These bring out the need to standardize SEO.
We need to standardize three things:
Open PageRank Computation
Crawl Data Portability
Open Rankings
These can help us improve our SEO expertise by sharing a common understanding with everyone in the industry.
Technical SEO in 2019
If you want to improve your technical SEO skills in 2019, here are some key things to consider.
Natural language generation can be a great ally in the future. We can take care of the good content and it can perfectly optimize it for the SERPs.
Semantic keyword research can also be helpful and it’s important to spend more time on it. It can even help you pull the right SEO metrics to draw better conclusions.
There are three types of tests that are most relevant to technical SEO:
Unit tests (testing an individual function to ensure that it works)
Integration tests (using your logic to build a bigger system)
UI tests (testing frontend interface on your website, which is the slowest version of testing)
Headless browsers can be very useful in the process of test-driven development. We tend to use them for Javascript-rendered content but they are actually made for automated testing.
From this perspective, we can think of technical SEO professionals as product managers. They are focusing on a test-driven development to run tests and experiment with different scenarios.
Here are some additional tips that have to do with technical SEO:
There will always be technical expectations for content that ranks well. We can deal these with the right text analysis, the perfect optimization and the content review that will lead to exactly what Google wants to see.
It’s useful to spend more time on automated testing, unit testing and also headless browsers. You can perform tests to see if they are how you expect them to be. It’s the idea of test-driven development that can help you check every single component.
Log file analysis is crucial. If you’re not doing it, then you’re just guessing.
PageRank is still our measurement. Even if we don’t have complete visibility, it’s still important to understand it.
We need to be proactive to understand Google. Don’t be afraid to dig into data to understand how Google works
Don’t underestimate the power of internal link building. The larger the page, the higher the success.
Tools to use in technical SEO
If you want to start using the right tools for technical SEO, here is the list that Mike provided in his presentation.
Ryte
Botify
Cognitive SEO
Chrome canary
Csvkit
Knime
MonkeyLearn
You can also find out more about free technical SEO tools in our own list.
Overview
What we need to remember when it comes to technical SEO is that it’s all about being curious. You don’t need to have a clear definition of your role and your tasks. These may depend on the company that you’re working for.
But you still need to be comfortable with figuring out how things work. You need to have the inquisitive mind to investigate why one thing succeeded over another.
And this is probably the best way to dive into it with the right mindset.
The post The state (or statelessness) of technical SEO in 2019 appeared first on Search Engine Watch.
from Digtal Marketing News https://searchenginewatch.com/2019/02/06/technical-seo-2019-statelessness/
0 notes
Text
PG Diploma Data Science using Python training course
Believe it or not, the fastest-growing use of Python is for data science. Behind the massive fan following of the Python lies numerous conditions. The most primary requirement is that Python is extremely easy to learn. While on the other hand, Data Science using Python is a nifty tool with a range of benefits. As it is open-source, Python's flexibility and continuous improvements with Data Science have become a genuinely resourceful option.
The other integrated languages like Java can also be used in this well-set structure. It is utterly helpful for your professional to take up data science training and enjoy a great future brimming with opportunities. It is crucial to get in touch with the best data science training institute in Bangalore for ideal support from the industry trainer in every possible way. Cranes Varsity is the top data science using python training institute where you'll not only learn but explore and build a future that will take you high in life with promising job placements.
Why is Python for Data Science the best?
Data science using python is in high demand across the globe. Few reasons can support the statement of why you should go for Data Science using Python as a great career option. There are notable advantages to learning this, which are all listed below;
1: Simplistic Approach
Python is very popular as a programming language mainly due to its simplicity. The best features are inherited with easy readability, making it a friendly language for beginners or freshers. It is time savvy which allows straightaway to get into the research part without spending most of its time in documentation. It is extensively used in statistical analysis, text processing, data analysis, web development, and much more.
2: One library for every sort of need
In Data Science using Python, the following is the most assorted library that makes it propelling to Data Science professionals. Python libraries include;
● NumPy is one of the most accessible libraries to find the use case in Data science.
● Pandas are built on the top of the NumPy.
● SciPy is the scientific equivalent of NumPy.
There are some more libraries like SymPy (statistical applications); Shogun, PyLearn2, and PyMC (machine learning); Bokeh, ggplot, Plotly, prettyplotlib, and seaborn (data visualization and plotting), and csvkit, PyTables, SQLite3 (data formatting and storage), to name a few.
3: It’s Multi-paradigm Approach
A great thing about Python is it's not limited to any programming language. The multi-paradigm feature makes it unique, which enables the support of functional, procedural, and objective-oriented programming & aspect-oriented programming style as well. With the data science certification, all this knowledge you'll gain eventually in training.
Who are all eligible for the data science online course?
Once you know about the immense benefits that you'll gather with the learning of Python in Data Science, you must be feeling to find out who is eligible for this? At Cranes Varsity, you can apply for the Data Science using Python training course if you are a working professional from an Engineering background, who is willing to increase your knowledge for better career aspects.
What is included in the data science training?
At Cranes Varsity, Data Science using Python training course syllabus is well-structured in terms of modules that will help the students better understand the subject. It includes:
● Relational Database - MySQL
● NoSQL - Mongo DB
● Web Technology - HTML, CSS, JavaScript
● Python Programming
● Advanced Python & Unit Testing
● Statistics
● Data Analysis & Visualization
● Machine Learning using SKlearn
● Deep Learning using Tenser Flow
● Tableau, Cloud Computing
You'll learn:
● Understand concepts like lambdas and CSV file manipulation.
● Describe standard Python data science functionality and features.
● For cleaning and processing, use DataFrame structures.
● Explain how t-tests, sampling, and distributions work.
About the PG Diploma in Data Science with Python at Cranes Varsity
The PG Diploma in Data Science using Python is a four-month professional program that provides solid knowledge and comprehension of Data Science. The expert teachers/ trainers have been industry leaders for decades. They offer instruction in all necessary disciplines so that engineers may create Java-based applications that satisfy industry standards
As the best data science training institute in Bangalore, Cranes provides students with an organized framework to help them improve their technical skills and knowledge curve. The lectures are well-planned and delivered using examples to make them more engaging and understandable. The goal is to help students develop more strong knowledge representations in their heads in Data Science using Python.
Choosing Crane s Varsity is ideal for you in many ways: ● Extraordinary faculty who are practically experienced for years and know in and out of the market trends.
● Online and offline assistance from time to time.
● All notes are provided related to the Data Science using Python
● Guaranteed placement to the top companies in the country
● Extensive study and knowledge sharing sessions
● Open discussions are appreciated
● Full-time assistance 24/7 over time
● Timely assessment
How valuable is the data science certification?
Once you have chosen the data science online course from Cranes Varsity, there is no looking back. Your qualifications will be valued at the best ways to the top class management where you can explore more opportunities. The chances of placement are guaranteed from the Cranes campus for those who complete the training successfully. Data Science using Python training course is not just a course. It is a promising way to advance with the trend and demands of employment opportunities for the long run.
The platforms used in the Cranes Varsity for offering Data Science Using Python are;
● Anaconda Distribution (Jupyter Notebook)
● Tableau
● MYSQL
● Mongo DB
● Google Colab
● AWS
Any data science using python training institute won't offer such versatility in the module designing and syllabus that covers so much, apart from Cranes Varsity. The placement opportunities are on a larger scale to the top organizations in the country. Do not wait and skip your chance; apply/register for the course today! With this helpful data science using python certification, you'll surely see a better career for yourself.
0 notes
Text
The state (or statelessness) of technical SEO in 2019
What do we need to know about technical SEO in 2019? Here’s an overview to keep in mind.
Technical SEO is different from what we know as standard SEO. It dives deeper into the analysis of content and it can help you draw very interesting conclusions.
Mike King from iPullRank delivered a highly informative presentation in Catalyst’s TechSEO Boost and it can give us a better idea of the state, or actually, the statelessness of technical SEO.
Whether you’re an SEO expert or you’re just getting started, here are some key points to consider from Mike’s session.
Defining technical SEO
The first challenge that comes with technical SEO has to do with its actual definition. It’s not always easy to explain it.
In fact, it’s even hard for SEO professionals to define it.
Mike King asked 300 people to provide their own definition to what technical SEO really is. Unsurprisingly, there was no consistency in its definition. Many respondents indicated that web performance and information architecture are parts of what technical SEO does. However, these are tasks that other roles typically perform.
As Mike King said, “everything we do is someone else’s job.”
The best way to define technical SEO as a profession then is to think of it as the state of being curious. Technical SEO experts are curious enough to play with things that they can change.
What we need to remember is that there is no technical SEO as a definitive discipline. It can be the job of putting things together to make things scale and solve problems that affect SEO.
Thus, if we want to explain the difference between technical and standard SEO, we need to remember that technical SEO is about scalability, depth, detail, advanced cross-functional understanding, and also execution.
The challenge of metrics
Another challenge that we’re seeing in technical SEO — and SEO in general sometimes — is that the metrics are too opaque.
There are many tools to measure our own definition of success but we still don’t have peer-reviewed and transparent definitions of any proprietary link metrics.
How can we tell which metrics matter most of all? How do we define success and how can we all agree to it?
These bring out the need to standardize SEO.
We need to standardize three things:
Open PageRank Computation
Crawl Data Portability
Open Rankings
These can help us improve our SEO expertise by sharing a common understanding with everyone in the industry.
Technical SEO in 2019
If you want to improve your technical SEO skills in 2019, here are some key things to consider.
Natural language generation can be a great ally in the future. We can take care of the good content and it can perfectly optimize it for the SERPs.
Semantic keyword research can also be helpful and it’s important to spend more time on it. It can even help you pull the right SEO metrics to draw better conclusions.
There are three types of tests that are most relevant to technical SEO:
Unit tests (testing an individual function to ensure that it works)
Integration tests (using your logic to build a bigger system)
UI tests (testing frontend interface on your website, which is the slowest version of testing)
Headless browsers can be very useful in the process of test-driven development. We tend to use them for Javascript-rendered content but they are actually made for automated testing.
From this perspective, we can think of technical SEO professionals as product managers. They are focusing on a test-driven development to run tests and experiment with different scenarios.
Here are some additional tips that have to do with technical SEO:
There will always be technical expectations for content that ranks well. We can deal these with the right text analysis, the perfect optimization and the content review that will lead to exactly what Google wants to see.
It’s useful to spend more time on automated testing, unit testing and also headless browsers. You can perform tests to see if they are how you expect them to be. It’s the idea of test-driven development that can help you check every single component.
Log file analysis is crucial. If you’re not doing it, then you’re just guessing.
PageRank is still our measurement. Even if we don’t have complete visibility, it’s still important to understand it.
We need to be proactive to understand Google. Don’t be afraid to dig into data to understand how Google works
Don’t underestimate the power of internal link building. The larger the page, the higher the success.
Tools to use in technical SEO
If you want to start using the right tools for technical SEO, here is the list that Mike provided in his presentation.
Ryte
Botify
Cognitive SEO
Chrome canary
Csvkit
Knime
MonkeyLearn
You can also find out more about free technical SEO tools in our own list.
Overview
What we need to remember when it comes to technical SEO is that it’s all about being curious. You don’t need to have a clear definition of your role and your tasks. These may depend on the company that you’re working for.
But you still need to be comfortable with figuring out how things work. You need to have the inquisitive mind to investigate why one thing succeeded over another.
And this is probably the best way to dive into it with the right mindset.
The post The state (or statelessness) of technical SEO in 2019 appeared first on Search Engine Watch.
from Digtal Marketing News https://searchenginewatch.com/2019/02/06/technical-seo-2019-statelessness/
0 notes
Text
The state (or statelessness) of technical SEO in 2019
What do we need to know about technical SEO in 2019? Here’s an overview to keep in mind.
Technical SEO is different from what we know as standard SEO. It dives deeper into the analysis of content and it can help you draw very interesting conclusions.
Mike King from iPullRank delivered a highly informative presentation in Catalyst’s TechSEO Boost and it can give us a better idea of the state, or actually, the statelessness of technical SEO.
Whether you’re an SEO expert or you’re just getting started, here are some key points to consider from Mike’s session.
Defining technical SEO
The first challenge that comes with technical SEO has to do with its actual definition. It’s not always easy to explain it.
In fact, it’s even hard for SEO professionals to define it.
Mike King asked 300 people to provide their own definition to what technical SEO really is. Unsurprisingly, there was no consistency in its definition. Many respondents indicated that web performance and information architecture are parts of what technical SEO does. However, these are tasks that other roles typically perform.
As Mike King said, “everything we do is someone else’s job.”
The best way to define technical SEO as a profession then is to think of it as the state of being curious. Technical SEO experts are curious enough to play with things that they can change.
What we need to remember is that there is no technical SEO as a definitive discipline. It can be the job of putting things together to make things scale and solve problems that affect SEO.
Thus, if we want to explain the difference between technical and standard SEO, we need to remember that technical SEO is about scalability, depth, detail, advanced cross-functional understanding, and also execution.
The challenge of metrics
Another challenge that we’re seeing in technical SEO — and SEO in general sometimes — is that the metrics are too opaque.
There are many tools to measure our own definition of success but we still don’t have peer-reviewed and transparent definitions of any proprietary link metrics.
How can we tell which metrics matter most of all? How do we define success and how can we all agree to it?
These bring out the need to standardize SEO.
We need to standardize three things:
Open PageRank Computation
Crawl Data Portability
Open Rankings
These can help us improve our SEO expertise by sharing a common understanding with everyone in the industry.
Technical SEO in 2019
If you want to improve your technical SEO skills in 2019, here are some key things to consider.
Natural language generation can be a great ally in the future. We can take care of the good content and it can perfectly optimize it for the SERPs.
Semantic keyword research can also be helpful and it’s important to spend more time on it. It can even help you pull the right SEO metrics to draw better conclusions.
There are three types of tests that are most relevant to technical SEO:
Unit tests (testing an individual function to ensure that it works)
Integration tests (using your logic to build a bigger system)
UI tests (testing frontend interface on your website, which is the slowest version of testing)
Headless browsers can be very useful in the process of test-driven development. We tend to use them for Javascript-rendered content but they are actually made for automated testing.
From this perspective, we can think of technical SEO professionals as product managers. They are focusing on a test-driven development to run tests and experiment with different scenarios.
Here are some additional tips that have to do with technical SEO:
There will always be technical expectations for content that ranks well. We can deal these with the right text analysis, the perfect optimization and the content review that will lead to exactly what Google wants to see.
It’s useful to spend more time on automated testing, unit testing and also headless browsers. You can perform tests to see if they are how you expect them to be. It’s the idea of test-driven development that can help you check every single component.
Log file analysis is crucial. If you’re not doing it, then you’re just guessing.
PageRank is still our measurement. Even if we don’t have complete visibility, it’s still important to understand it.
We need to be proactive to understand Google. Don’t be afraid to dig into data to understand how Google works
Don’t underestimate the power of internal link building. The larger the page, the higher the success.
Tools to use in technical SEO
If you want to start using the right tools for technical SEO, here is the list that Mike provided in his presentation.
Ryte
Botify
Cognitive SEO
Chrome canary
Csvkit
Knime
MonkeyLearn
You can also find out more about free technical SEO tools in our own list.
Overview
What we need to remember when it comes to technical SEO is that it’s all about being curious. You don’t need to have a clear definition of your role and your tasks. These may depend on the company that you’re working for.
But you still need to be comfortable with figuring out how things work. You need to have the inquisitive mind to investigate why one thing succeeded over another.
And this is probably the best way to dive into it with the right mindset.
The post The state (or statelessness) of technical SEO in 2019 appeared first on Search Engine Watch.
from Search Engine Watch https://searchenginewatch.com/2019/02/06/technical-seo-2019-statelessness/
0 notes