Google Analytics was introduced in 2005 and has been the go-to tool for tracking business and website performance data for a long time. With time, we have seen significant improvements in how we analyze and comprehend consumer behavior online.
Now, Google is introducing the next level of website analytics: Google Analytics 4 (GA4), a new and enhanced platform version. Get ready to take your data analysis to the subsequent level with GA4.
Nevertheless, there is an important date coming up – July 1st, 2023, the probable launch of GA4. So, it is the best time to talk about why you should migrate to this new platform. Let us dive in!
Why should I think of making the Switch to Google Analytics 4?
As a website or business owner you know the value of harnessing data analytics, and you want to keep more close watch on your precise performance, conversions, and user activity. In this blog, you will explore more about why you should consider upgrading to GA4.
On July 1st, Google’s Universal Analytics (UA) will stop gathering data, and all previous data will disappear after six months. But do not fear!
Switching over to Google Analytics 4 (GA4) will keep you in the loop on the success of your digital marketing efforts. Plus, come July, you can easily compare user engagement stats with last year’s metrics. So, better keep your data analytics game strong by switching to GA4!
Discover the Critical Distinctions: Universal Analytics vs. Google Analytics 4!
Although both platforms provide insights into website performance, there are noteworthy differences between Universal Analytics and Google Analytics 4. Here are the key distinctions to know.
Data Privacy: You can boost your data privacy with GA4, staying compliant with GDPR and CCPA regulations.
Cross-device monitoring: GA4 will offer cross-device monitoring abilities enabling digital marketers to better comprehend the user journey across devices.
Machine Learning (ML): GA4 comprises ML algorithms that automatedly find trends, craft insights, and offer recommendations.
Behavioural Modeling: It will leverage machine learning and seal in the gaps if cookies are not accessible in GA4’s reporting features.
Customized Channel Grouping: You can customize channels and match combined performance.
Integrations: GA4 integrates directly with Google Ads and will enable reporting dashboard for performance clarity.
Key Gains from Google Analytics
Have you ever wondered why Google Analytics 4 would come into existence after years of using Universal Analytics? GA4 is a whole new analytics tool that can provide digital marketers with valuable insights previously unavailable. Keep reading to discover the benefits and gains Google Analytics 4 will offer the user base.
Track user behavior with web and app analytics in GA4
Analyze user journey with Google Analytics 4
Create GA4 custom reports for better insights
Save time with automated event tracking
Access advanced user properties in GA4
Use predictive metrics to optimize your strategy
Integrate with BigQuery for free and analyze huge datasets.
What to do next for the upcoming arrival of GA4?
Now you better know that GA4 is on its way. However, do not wait until the last minute to prepare for the significant change. We suggest you start transitioning to the new Analytics world as soon as possible. Trust our words as time flies by swifter than you think.
Just a heads up – when Google Analytics 4 is fully implemented, Universal Analytics will no longer be accessible. But do not worry. You can still use UA and GA4 together until July 2023.
So why not take benefit of the opportunity now to dive into the new features of GA4 alongside your current data? It is the ideal time to explore and stay ahead of the curve.
However, better hold up. There is no need to fear or freak out. We understand that the news of Google ending UA tracking may sound overwhelming, but fear not! Our team is here to guide you through it all.
Moving Forward with Google Analytics 4 (GA4)
Ready to upgrade your Google Analytics game? The LogicRays team is here to help! Whether you need to discuss the migration strategy of your account to GA4 or learn more about it, we have got you covered.
Please do not wait until it is extremely late. Make the change and start gaining valuable insights for your business today. Contact us to get quickly started!
Hola business people, it’s 2022 & there is no surprise in accepting the fact that how digital media is evolving like never before. And, of course, there is no option of not making the most out of it. Don’t you agree with that? #TechGoals. In this fast-paced life, not everyone reads a blog containing 1500+ words. Hence, podcasts for your business can serve some real fruitful benefits. Imagine your website users listening to podcasts for your business (Consuming your content) while driving, or while cooking (and understanding it). How interesting, isn’t it?
Plan A Well Structured Podcasts For Your Business
Hey people, don’t be in a hurry. First things first, you ought to structure the podcasts for your business well. From deciding the topics to the objective behind each episode. From the clip art to the length of your small business podcasts. Also, there are tons of things you can play through podcasts, from introducing chat shows to giving a new creative touch. After all, it’s the podcasts for your business; play with it well.
How & Where To Put Your Podcasts For Business
Just as you embed a Youtube video on your website page, the same goes for the podcasts for your business. It’s all up to you. Say, for example, if you have an educational website, you can put the podcasts in between the blogs. It goes without saying that there are some major audio platforms in your business podcast that can be live, like; Spotify, Anchor, Amazon, & so on.
Benefits of Podcasting (For Your Business)
See, the benefits of podcasting are endless. But one should not look at it just from the profit part. You gotta create some really good content. You gotta win the audience rather than just publishing back-to-back content.
Anywhere Anytime
The major thing about podcasting for your business is users can listen to them from anywhere at any time.
Boosting Your Personal Connection
Undoubtedly, the introduction of the podcast with your users might help you to form a whole different level of connection as they are not just reading. They are experiencing your content in a different sort of vibe. (explain the vibe)
Attract more customers through
Once you start a podcast, & if you are consistent with posting quality content then there are high chances that people may visit your website more or their curious heads want to know more about your stuff. Also, if they like your content, they may share it with others, resulting in more traffic.
A New Way for your Brand Awareness
Nowadays, the sources of your discoverability have increased tremendously. Through audio platforms, your podcast can reach many, hitting the right type of audience and creating great brand awareness. This can be a significant game of podcasts for your business.
And there is a whole different psychology behind it. Listeners will see your brand’s artwork, probably your brand name in your episodes & they would get an idea of what the base of your brand is. Indicating that you’ve sold a product without even selling it. If you know, you know your podcasts for your business would rock!
Alternative of Video
We all know the impact of videos since a few years ago is something truly dope. There are various things that get involved while making the video content. But the thing is, it is more time-consuming and it requires a lot of involvement from many. Podcasting can be easier to create & the thing is, it is emerging incredibly strong.
One secret is you can create your business podcast both through audio and video form. This will give a choice to the listeners based on their suitability. Your duty is to post the content in whichever style you want. Freedom, cool processes, ideas, and innovations will be on the top.
The Freedom of Creativity
Whether you’re an IT firm or running an independent artist community, you have full power to shower your creativity and come up with extraordinary content. Hence, from a creative perspective, there is hardly anything that can beat podcasts.
And as mentioned, podcasting is something that you can listen to while doing your own thing. Sometimes it is ok if you don’t pay your full attention based on the content you’re listening to. Also, nowadays, there are Alexa and google devices in which you just need to say what you need to listen & then that device will play your chosen podcast. It’s so simple!
The other thing is, it is free. Similar to youtube, you don’t need to pay anything in order to create your podcast account. Therefore, we advise you to create your account if you haven’t yet so that you won’t need to regret it later.
Additional Revenue
Once your podcast becomes a hit or gets enough reach, there is no looking back. Although in many countries, you cannot earn through podcasting directly. However, we are not talking about monetization. There are many additional zones in which you can try your hands on.
Paid Partnership
Natural Brand Reach
Paid Partnership
What if you get paid for the thing you love doing the most? The same goes for podcasting. Once you get a good reach and create a good audience, you can actually look for sponsorships. You just need to call out the sponsor’s name in the episode and some other formalities & you are done. Yes, it is that simple. A simpler example would be, that you are just investing your content in the market that is gonna pay you back if you exceed certain criteria.
And it is an easy game, that the more consistent you are, there are more chances of your growth. This will attract more sponsorships and the chances of affiliate marketing are more. Overall, there is no guarantee in this but there is another door, waiting for you with endless opportunities that you need to at least try unlocking. Hence, have hopes and belief in the content you’re making then only you would be able to crack the sponsorships.
Natural Brand Reach
More content> more reach> more audience > more reach > more recognition > more curiosity > more brand awareness and more sales!
Got More Questions About Creating Podcasts For Your Business?
We understand your concerns; there must be a bucket full of questions in your head like how to start a podcast for your business? What topic will suit you best for your business podcasts? & so on. Nothing to worry about. Let the podcasts for your business rock on every major audio platform through extraordinary content!
From designing a website for your business to adding some amazing new features like; podcast only, we can do it all for you. Connect to our expert team now!
“Python Language Is One Example. As We Noted Above. It Is Also Heavily Used For Mathematical And Scientific Papers. And Will Probably Dominate That Niche For Many Years Yet. – Eric S. Raymond”
Wherever you go, Python is everywhere!
So, Why is Python a best fit for Big Data?
Python is designed in a way that is easy to write and read. Not being a complex language, gives it the benefit of more usage. According to Stack Overflow Trend, Python is acknowledged as the fastest-growing programming language.
Python is an interpreted, open-source, general-purpose, and object-oriented programming language. creating the world’s top applications such as Instagram, Google, Spotify, Uber, Pinterest, Reddit, etc.
Big data is the most precious commodity in this era. Someone said that “The Future of IT is Big Data”, well that is true, but how?
Let’s start with the basics of “What exactly Big Data is?”.
“Big Data is a huge cluster of data that is enormous in size and volume.”
The raw data comes with a large size and numerous complexity that no traditional tool can store, handle, and process it precisely. In short, Big data is data of large size.
Big size companies possess a huge bundle of data, where processing, and analyzing it can take a pretty much large amount of time, and the results may not be precise. Selecting a programming language for Big Data is a project-specific task, that depends on its goal. It doesn’t matter what projects, Python is best fit for Big Data.
But Why Python for Big Data?
When people started combining Python and Big Data, the scenario of the marketplace changed and now, Big Data is much more efficient and easy to understand, because Python has made it easy to use and understandable for every developer. Python is in enormous demand among all Big Data Companies right now.
Here, we will discuss why using python for Big Data is beneficial.
#1 Open- Source
Open source is software in which the original code is released under a license. This code can be altered, modified, and enhanced according to developers needs.
Python is an Open source programming language, thus, it supports multiple platforms. Python also supports environments like Linux, Windows, and MacOS.
Instead of wasting time in technical terms of language, the simple, clean, and readable syntax helps Big Data experts to focus on case managing Big data easily. This is one of the main reasons to opt for Python for Big Data.
Most Popular Programming Languages
#2 Simple and Minimal Coding
Minimal codes in Python programming make it extensively used, compared to other languages that are available for programming. Python is known for its execution in a few lines of code. Moreover, it automatically provides help to associate and identify various data types.
If you or someone has an idea, all you have to do is think and write 5-10 lines of code and there you go! Your program is ready to use.
This programming language follows an indentation-based nesting i.e. structure instead of braces to structure any program in it. This language can bear a heavy and complicated task in just a click of time. That data computes in commodity machines, clouds, desktop, and laptop.
In the beginning, python was considered a slow language compared to its equivalents like Scala and Java. Now, the scenario has taken a turn of 360 since then.
When Anaconda platform arrived in market, it came with a great speed to analyze the code. This is why Python for Big Data became the best option for everyone.
Your Python project works best when you Hire Python Developer who can add the essence and benefits of python in your business.
#3 Speed
Python is highly popular for its high speed to analyze the code and for software development. The precision of Python to analyze code is perfect, because of that Python is the most appropriate choice for Big Data. It supports prototyping ideas that help to make the code run faster.
While doing so, Python also maintains the transparency between the process and the code.
After Anaconda entered the market, the whole scenario of working on python language changed. It came with a speed that made everything in it useful. Python programming makes sure that the code is transparent and readable.
Such speed made python more powerful, and Big Data can use that speed to make the development faster.
#4 Libraries of Python for Big Data
Python offers a large set of standard libraries that includes corners like stings operations, internet protocols, operating system interface, and web service tool.
The standard library sets contain frequently used programming languages to make coding easier and smaller.
Python provides multiple useful libraries of your wish. This makes Python a famous programming language in the area of scientific computing.
Big data, as the word suggests, it involves a huge amount of data analysis and computation. These libraries make the work easier for Big Data Analytics.
Python offers numerous pre-tested analytics libraries. Big Data Analytics uses these libraries filled with packages, such as:
Data Analysis: Inspecting, cleaning, modeling, and transforming any size of data (Large or Small) to discover some useful information for predicting the future of business on the basis of current information.
Statistical Analysis: It is the process of collecting and analyzing the data, in order to analyze the trend and pattern.
Machine Learning: As the name suggests, ML is programming a computer in such a way that it learns everything from different kinds of data on its own. Machine Learning uses python libraries like Numpy, Scikit-learn, Theano, TensorFlow, Keras, Pandas, PyTorch, and Matplotlib.
Numerical Computing: Scientific computation is done by this. Scientific computing contains Scipy, Pandas, IPython, Natural language Toolkit, and Numeric python.
Data Visualization: It gives many insights that data alone cannot provide. When you visualize the information, you bring your mind into the landscape that you explore with your eyes, like an information map in front of your eyes. Visualization libraries contain Matplotlib, Plotly, Seaborn, ggplot, and Altair.
Library Features
#5 Compatibility of Python with Hadoop
Hadoop’s framework is made using Java programming language. Hadoop programs also use C++ and Python. It means that even if the data architects don’t know anything about java, they can use python as an option. When you compare Java with Python, it is much easier to use python because of its small codes and high speed.
Compared to other programming languages, Hadoop is more compatible with python. You can incorporate all the features into your business. For this, you will have to Hire Python Developer who is good with the skills.
About Pydoop Package
Pydoop package is an interface of python to hadoop that gives you authority to write MapReduce applications and interact with HDFS applications in python.
HDFS API let’s you write and read different information on directories, global file system properties without facing any problem.
Pydoop provides MapReduce API for solving tough and complex problems with minimal programming. This API implements advanced data science concepts like ‘Record Reader’ and ‘Counter’, which makes Python the best fit for Big Data.
#6 Data Processing Support
Python comes with an inbuilt feature of supporting data processing. Data processing for unconventional and unstructured data. uses this feature. This is the main reason why big data analytics companies choose python over every option.
#7 Scope of Python for Big Data
Python is an object-oriented language that supports high-level data structures. It allows users to simplify all data operations. Python manages some of the data structures i.e. lists, dictionaries, tuples, sets, etc. Other than this, Python also supports scientific computing operations such as data frames, matrix operations, etc.
These astonishing features of Python help to enhance the scope of language by enabling it to increase speed of data operations. This makes Python and Big Data the most charming and useful combination. That’s why python a best fit for Big Data.
Stack Overflow
Before We Apart
Now, You may have a clearer picture in front of you now about why Python is best fit for Big Data. To understand it more clearly, you will have to go deep into it and understand every single bit of it because Big Data is like a star in the universe, no matter how far you go, it will never reach its limit of learning.
“Data is a precious thing and will last longer than the systems themselves.”- Tim Berners-Lee
Big Data technology is spreading across the world, people are learning and advancing themselves every day. It can be a very flinty task, but knowing why Python a best fit for Big Data will for sure help you make your way through learning Big data using Python.
