Data Analytics Technology Updates

Data interactions have multiplied by 5000% from 2010 to 2020. With increasing consumers interacting in the digital space, a gold mine of user information is present for business intelligence services.

This has compelled an increasing number of businesses to become data-driven. With the growth in the importance of data over instinct, data analytics technology is also enhancing its pace.

The blog explores how data can transform your business and highlights the importance of this data in the business world. 

By delving into data analytics technology updates, you can learn better to manage and use your data to boost your business. We have identified three  advanced data analytics solutions

This guide is mainly made to help business executives understand the new data analytics technology and provide resources to empower them to use data better.

Data Analytics Technology Updates

1. Google Analytics 4 (GA4):

Google Analytics 4, commonly known as GA4, is a new Google property that gives importance to the customer journey. Google has decided to sunset its Universal analytics by July 1, 2023 and has replaced it with GA4.

If you are using google analytics, you must consider GA4 migration to benefit from robust and new features and to prevent data loss.

This tool is undoubtedly a treasure trove of valuable data for businesses. GA4 represents a significant shift in the way data is collected and analyzed, offering more advanced features and capabilities compared to its predecessor.

Unlike the previous version of Google Analytics, this property is event-based, which means it is more focused on user action than user visits. It can be used to track the data of multiple devices.

Google is providing free GA4 migration to its clients. However, there is only so much one can do with automated support and delayed responses from Google representatives.

It is essential that clients with complex tracking infrastructure and ecommerce data collection seek expert help to make sure that they receive proper guidance and accurate implementation.

Data-driven businesses depend on accurate data to make major decisions, and with embedded layers of tracking, there are many things that could go wrong during migration to GA4.

How is it useful for business owners:

What is new and What remains the same?

GA4 has enhanced cross-platform tracking capabilities. Unlike the traditional GA, GA4 allows businesses to track user interactions across multiple devices and platforms, including websites, mobile apps, and even offline interactions.

This holistic view of user behavior provides a more comprehensive understanding of customer journeys and enables businesses to optimize their marketing strategies accordingly.

There are many changes that are coming with GA4, while there are many reports that are the same as Universal analytics. Among the big changes that are visible to the users are:

Overall, GA4 is more user-friendly but it will take some time for the users to acclimatize to it. It is made with the primary objective to protect individual data

2. Microsoft Fabric:

Microsoft Fabric brings AI into data. It is a cloud service that brings data management services to your fingertips in one place. It is one place to discover and manage your data, a perfect turnkey option for all information.

If you are familiar with Microsoft data services, Microsoft leveraged the three existing Microsoft platforms: Power BI, Synapse Analytics, and Data Factory.

It took them to the next level with Microsoft Fabric. Microsoft Fabric is unique because it is a data lake that can be used across different workloads.

It is an end-to-end analytics solution with full-service capabilities including data movement, data lakes, data engineering, data integration, data science, real-time analytics, business intelligence and data visulization services all backed by a shared platform providing robust data security, governance, and compliance.

With the help of advanced data  analytics solutions and the technology updates in data analytics, it will be easier for companies to collect this unstructured data using tools such as Power Bi consulting.

How is it useful for business owners:

Fabric is aimed at removing glitches in connecting different tools in a data analytics ecosystem. The lake-like architecture provides for more flexibility in handling data, but the embedded AI aims to give a better structure to unstructured data in a more seamless and intuitive manner.

As the product gains traction and more users migrate their data to take advantage of this all-encompassing tool (as it promises), it will be interesting to see if the AI stands the test of time.

Google Bard and ChatGPT

Google’s Bard has tried to catch-up with the latest advancements in AI led by OpenAI’s ChatGPT and the slew of plugins that it has enabled. Bard is a conversational AI chatbot that can generate text of all kinds.

Bard has not replaced Google Assistant, but it is much more formidable. Bard is based on its own Large Language Model known as LaMDA which has been trained on billions of data points and parameters.

However, Bard is still in the experimental phase and is continuously being trained on feedback from the common public. ChatGPT has been proven to ease in which data analytics is pursued.

It has the potential to revolutionize complex functions like integration, querying, cleaning and even visualization.

Google explicitly mentions that Bard is not yet optimized for coding tasks and there may be a future where Bard is more capable on this front. There have been some experiments to compare how Bard fares against ChatGPT to accomplish data analytics workflows and functions.

For example, when asked to make a given code in SQL more efficient, Bard was able to provide 10 different solutions, all of them being sensible. 

But when Bard was asked to explain a common syntax error in an R code, it was unable to provide any help. Similarly, when it was asked to explain a line of code written in Python, it failed to do so. This is where ChatGPT was able to ace both tasks.

In another example. Bard was asked to act as a data scientist and asked to write a simple query to count users based on different categories. 

Surprisingly, it was able to provide the code followed by an explanation. Interestingly, when Bard was subjected to work on a more nuanced query, it provided three probable solutions, at least one of which turned out to be a correct option.

When tested for data visualization services, Bard again provided the answer when asked to ‘create a scatter plot’. However, when asked to draw a line plot using a gapminder dataset, Bard got confused in assigning a parameter as a column or an index despite being prompted in the command.

Hence, Bard is able to accomplish certain simpler data analytics functions. But it still has a long way to go in being a leader in the field of data analytics. ChatGPT is ahead in the game for now.


Bard vs ChatGPT for Data Science

What is Google Bard? Here’s how to use this ChatGPT rival

Final Thoughts

Harnessing the power of Advanced Data Analytics Solutions can be a game-changer for businesses, enabling them to unlock valuable insights and enhance their operations through data-driven decision-making.

It’s no secret that leading businesses and industry giants understand the importance of data and leverage it to drive success.

By staying up-to-date with the latest advancements in data analytics technology and partnering with a team of experts, businesses can access high-quality data analytics services that can drive growth and innovation.

If you’re seeking reliable solutions, consider connecting with Quilytics, a reputable data analytics company serving businesses in the US. We are dedicated to providing top-notch data analytics services, empowering businesses to make informed decisions and thrive in today’s data-driven landscape. Reach out to us to learn more about our solutions and how we can help your business succeed.