There are a ton of laptops on the market at any given moment, and almost all of those models are available in multiple configurations to match your performance and budget needs. So if you’re feeling overwhelmed with options when looking for a new laptop, it’s understandable. To help simplify things for you, here are the main things you should consider when you start looking.

Price

The search for a new laptop for most people starts with price. If the statistics chipmaker Intel and PC manufacturers hurl at us are correct, you’ll be holding onto your next laptop for at least three years. If you can afford to stretch your budget a little to get better specs, do it. And that stands whether you’re spending $500 or more than $1,000. In the past, you could get away with spending less upfront with an eye toward upgrading memory and storage in the future. But laptop makers are increasingly moving away from making components easily upgradable, so again, it’s best to get as much laptop as you can afford from the start. 

Generally speaking, the more you spend, the better the laptop. That could mean better components for faster performance, a nicer display, sturdier build quality, a smaller or lighter design from higher-end materials or even a more comfortable keyboard. All of these things add to the cost of a laptop. I’d love to say $500 will get you a powerful gaming laptop, for example, but that’s not the case. Right now, the sweet spot for a reliable laptop that can handle average work, home office or school tasks is between $700 and $800 and a reasonable model for creative work or gaming upwards of about $1,000. The key is to look for discounts on models in all price ranges so you can get more laptop for less. 

Operating system

Choosing an operating system is part personal preference and part budget. For the most part, Microsoft Windows and Apple’s MacOS do the same things (except for gaming, where Windows is the winner), but they do them differently. Unless there’s an OS-specific application you need, go with the one you feel most comfortable using. And if you’re not sure which that is, head to an Apple store or a local electronics store and test them out. Or ask friends or family to let you test theirs for a bit. If you have an iPhone or iPad and like it, chances are you’ll like MacOS too. 

But when it comes to price and variety (and, again, PC gaming), Windows laptops win. If you want MacOS, you’re getting a MacBook. While Apple’s MacBooks regularly top our best lists, the least expensive one is the M1 MacBook Air for $999. It is regularly discounted to $750 or $800, but if you want a cheaper MacBook, you’ll have to consider older refurbished ones. 

Windows laptops can be found for as little as a couple of hundred dollars and come in all manner of sizes and designs. Granted, we’d be hard-pressed to find a $200 laptop we’d give a full-throated recommendation to, but if you need a laptop for online shopping, email and word processing, they exist. 

If you are on a tight budget, consider a Chromebook. ChromeOS is a different experience than Windows; make sure the applications you need have a Chrome, Android or Linux app before making the leap. But if you spend most of your time roaming the web, writing, streaming video or using cloud-gaming services, they’re a good fit. 

Size

Remember to consider whether having a lighter, thinner laptop or a touchscreen laptop with a good battery life will be important to you in the future. Size is primarily determined by the screen — hello, laws of physics — which in turn factors into battery size, laptop thickness, weight and price. And keep in mind other physics-related characteristics, such as an ultrathin laptop isn’t necessarily lighter than a thick one, you can’t expect a wide array of connections on a small or ultrathin model and so on. 

Screen

When it comes to deciding on a screen, there are a myriad considerations: how much you need to display (which is surprisingly more about resolution than screen size), what types of content you’ll be looking at and whether you’ll be using it for gaming or creative work.

You really want to optimize pixel density; that is, the number of pixels per inch the screen can display. Though there are other factors that contribute to sharpness, a higher pixel density usually means sharper rendering of text and interface elements. (You can easily calculate the pixel density of any screen at DPI Calculator if you don’t feel like doing the math, and you can also find out what math you need to do there.) We recommend a dot pitch of at least 100 pixels per inch as a rule of thumb.

Because of the way Windows and MacOS scale for the display, you’re frequently better off with a higher resolution than you’d think. You can always make things bigger on a high-resolution screen, but you can never make them smaller — to fit more content in the view — on a low-resolution screen. This is why a 4K, 14-inch screen may sound like unnecessary overkill but may not be if you need to, say, view a wide spreadsheet.

If you need a laptop with relatively accurate color, that displays the most colors possible or that supports HDR, you can’t simply trust the specs — not because manufacturers lie, but because they usually fail to provide the necessary context to understand what the specs they quote mean. You can find a ton of detail about considerations for different types of screen uses in our monitor buying guides for general purpose monitors, creators, gamers and HDR viewing.

Processor

The processor, aka the CPU, is the brains of a laptop. Intel and AMD are the main CPU makers for Windows laptops, with Qualcomm as a new third option with its Arm-based Snapdragon X processors. Both Intel and AMD offer a staggering selection of mobile processors. Making things trickier, both manufacturers have chips designed for different laptop styles, like power-saving chips for ultraportables or faster processors for gaming laptops. Their naming conventions will let you know what type is used. You can head to Intel’s or AMD’s sites for explanations so you get the performance you want. Generally speaking, the faster the processor speed and the more cores it has, the better the performance will be.

Apple makes its own chips for MacBooks, which makes things slightly more straightforward. But, like Intel and AMD, you’ll still want to pay attention to the naming conventions to know what kind of performance to expect. Apple uses its M-series chipsets in Macs. The entry-level MacBook Air uses an M1 chip with an eight-core CPU and seven-core GPU. The current models have M2-series silicon that starts with an eight-core CPU and 10-core GPU and goes up to the M2 Max with a 12-core CPU and a 38-core GPU. Again, generally speaking, the more cores it has, the better the performance. 

Battery life has less to do with the number of cores and more to do with CPU architecture, Arm versus x86. Apple’s Arm-based MacBooks and the first Arm-based Copilot Plus PCs we’ve tested offer better battery life than laptops based on x86 processors from Intel and AMD.

Graphics

The graphics processor handles all the work of driving the screen and generating what gets displayed, as well as speeding up a lot of graphics-related (and increasingly, AI-related) operations. For Windows laptops, there are two types of GPUs: integrated (iGPU) or discrete (dGPU). As the names imply, an iGPU is part of the CPU package, while a dGPU is a separate chip with dedicated memory (VRAM) that it communicates with directly, making it faster than sharing memory with the CPU.

Because the iGPU splits space, memory and power with the CPU, it’s constrained by the limits of those. It allows for smaller, lighter laptops, but doesn’t perform nearly as well as a dGPU. In fact, there are some games and creative software that won’t run unless they detect a dGPU or sufficient VRAM. Most productivity software, video streaming, web browsing and other nonspecialized apps will run fine on an iGPU, though.

For more power-hungry graphics needs, like video editing, gaming and streaming, design and so on, you’ll need a dGPU; there are only two real companies that make them, Nvidia and AMD, with Intel offering some based on the Xe-branded (or the older UHD Graphics branding) iGPU technology in its CPUs.

Memory

For memory, we highly recommend 16GB of RAM (8GB absolute minimum). RAM is where the operating system stores all the data for currently running applications, and it can fill up fast. After that, it starts swapping between RAM and SSD, which is slower. A lot of sub-$500 laptops have 4GB or 8GB, which in conjunction with a slower disk can make for a frustratingly slow Windows laptop experience. Also, many laptops now have the memory soldered onto the motherboard. Most manufacturers disclose this, but if the RAM type is LPDDR, assume it’s soldered and can’t be upgraded. 

However, some PC makers will solder memory on and also leave an empty internal slot for adding a stick of RAM. You may need to contact the laptop manufacturer or find the laptop’s full specs online to confirm. And check the web for user experiences, because the slot may still be hard to get to, it may require nonstandard or hard-to-get memory or other pitfalls.

Storage

You’ll still find cheaper hard drives in budget laptops and larger hard drives in gaming laptops, but faster solid-state drives have all but replaced hard drives in laptops. They can make a big difference in performance. But not all SSDs are equally speedy, and cheaper laptops typically have slower drives; if the laptop has only 4GB or 8GB of RAM, it may end up swapping to that drive and the system may slow down quickly while you’re working. 

Get what you can afford, and you likely need less than you think. If you need to go with a smaller drive, you can always add an external drive or two down the road or use cloud storage to bolster a small internal drive. The one exception is gaming laptops: We don’t recommend going with less than a 512GB SSD unless you really like uninstalling games every time you want to play a new game. 





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What is Power BI?

Power BI is one of the popular business intelligence tools developed by Microsoft Corporation to offer various data modeling capabilities like data preparations, data visualizations, data discovery, and generating interactive data analytic dashboards. With the help of Power BI users can make powerful business-related decisions. This Power BI tool helps users to pull the data using various formats such as images, excel sheets, spreadsheets, and videos. The Power BI tool also helps to centralize the database management system, and you can also visualize the data model on it.

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What is Google data studio?

Google data studio is an easy-to-use tool that is used to create a beautiful data visualization within a minute. This is a cloud-based application that can be run on the various top web browsers like chrome, safari, and firefox. This type of tool is able to deliver stunning, and insightful reports without much action from the user. Google data studio also comes up with a free-to-use license for personal or commercial use. With the help of Google data studio dashboard, you can access various types of charts such as charts, bars, pie, lines, Areas, scatter, etc, and this also adds up value to the data reports.

Comparison of Power BI and Google data studio:

Here we are going to explain the major comparison between power BI and Google data studio based on a few functionalities. Let’s start it;

Installation:

Power BI tool has a number of ways to install or configure it, and it all depends on the license. The basic, and very best way to install Power BI as a desktop application on your desktop. Power BI application is quick and straightforward so all you need is just a modern PC with 4GB of RAM (ideally 8GB of RAM) and running windows 8 operating system version or later. Power BI is a Microsoft product, and it is not available for MAC operating systems. 

Google data studio is completely web-based, so you do not need to install it on your computer/pc. Directly you can access them by logging into the Google page like other Google products. 

Data source:

Power BI consists of various pre-built connectors, and they enable you to connect to a wide variety and ever-expanding data sources. PowerBI’s web connectors help you to import data from almost any data source that includes Amazon, Google, and other Microsoft competitors.

Whereas Google data Studio data connectors are much smaller and offer only 18 connectors that are built by Google. inc itself. There are also 400+ connectors built by Data studio partners. These types of connectors you get to see only for advertising, media, and content-related websites.

Data transformation:

Power BI offers a full range of data transformations by using a power Query engine. Power Query lets you perform ETL (Extract, transfer, and loading) operations on the data which you have and prepare it for visualization. Users can also make use of data analysis expression (DAX) to build formulas and expressions. Power BI has a lot of capabilities to perform data transmission operations. 

Whereas Google data studio lags behind this feature. In Google data studio, the only way to perform data transformation is by using JOIN keys. So by default google assumes that you already have clean data for the visualization.

Ease of use:

If you are familiar with MS Excel, then Power BI would be a great choice.  But to access power BI, some sort of struggle is required to connect and integrate with different data sources. Power BI has also offered better functionalities than the Google data studio and also helps you with a drag-and-drop feature. 

Whereas Google data studio is very easy to navigate and the learning curve is minimal. The user interface of this platform is extremely intuitive as long as you have clean datasets. Only one thing you need to concentrate on is a drag-and-drop feature that helps you to create quick reports.

Sharing:

In Power BI report sharing is a complex task that is compared to the Google data studio. The biggest concern is that it is impossible to share a report directly from the desktop applications. Every time you need to publish the reports in the Power BI services. However mobile applications let you share a dashboard or report directly from the application.

In power BI you can share your reports and dashboards with internal and external collaborators. 

On the other hand, sharing data with google data studio is an easier task. With the help of email or links, you can share the reports in the Google data studio. In google, the recipients dont need to pay any subscription fees because Google offers a free google data studio tool.

Mobile compatibility:

Power BI consists of the native applications for Android, Windows, and IOS smartphones. In Power BI smart mobile application, you can perform the below vital tasks:

  • Visualizing data reports
  • Filtering of the data from a report.
  • Adding notes to the reports.
  • Getting a notification and setting alerts.
  • Exploring on-premise data reports.

Whereas Google data studio does not have a mobile application version so that users can visualize the data reports using the mobile browser, editing the report could be a challenging task. 

Community and online resources:

We already know that Microsoft Power BI has a huge knowledge base community to learn and resolve the issues about the platform usage. When you login into the communities, you will get to see a lot of content which are related to the platform guide. For example, themes gallery, custom visual studios, data stories gallery, developer, etc.

Similarly, Google data studio also has robust communities. Here the community gallery section of this tool gives you access to various third-party visualization widgets. 

Cost:

Power BI desktop is free but can be accessed only by beginners who want to know the basic things about the tool. For the business purpose, you need to share a desktop, and the cost it will going to charge is $9.99 per user/per month (premium subscription). Power BI Pro is a cloud-based application that can be used for collaboration, sharing, publishing, etc. If you are an expert, and you want power BI for both the on-premise and cloud-based reporting, support for big data and analytics, dedicated cloud computes, and storage resources you can opt for Power BI premium at $4995/year. 

Whereas the Google data studio is free to use application. And all you need is just a Google account.

Functionalities:

Power BI tool is available for both beginners and advanced level experts due to its tons of data manipulation features. It also helps you to access data through the data visualization elements like charts, bars, tables, graphs, etc. one more functionality of the Power BI is, the tool gets refreshed itself  8 times a day.

Whereas Google data studio comes up with fewer features when compared to the Google data studio as it is only a data visualization application. However, its in-memory BI engine is a powerful feature that helps users to eliminate the data visualization lags, especially used for the larger number of data sets. The Google data studio application gets refreshed itself every 12 hours.

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Pros and Cons of the Power BI:

First, let’s start with the Power BI:

Advantages of the Power BI:

Below are the primary advantages of the Power BI:

Offers easy data exploration and data visualization:
This is the world of data exploding, this tool offers the ability to explore valuable data and also perform data visualization tasks to get greater results. When compared with other business intelligence tools, I think this is an awesome tool in the data visualization process.

Acts as a managed self-service Business intelligence tool:
This Microsoft business intelligence tool provides an effective self-service business intelligence tool. The MSBI also acts as a Microsoft Excel that is used by everyone in their day-to-day activities to produce and report the data analytics.

This tool makes use of Native MS excel features:
The MSBI tool makes use of Microsoft Excel features to the core in order to produce effective data analysis. By using excel Microsoft excel features it’s very easy to collect data from multiple data sources.

MSBI tool supports Web service applications:
MSBI tool works well with programming languages like .NET and SQL database servers to build an effective web service application and also offers abundant benefits to the clients.

End-to-end Business solutions:
MSBI provides you with a great business solution for your organization and enables users to make effective business decisions. This tool offers entire top-to-bottom business solutions.

Data warehouse applications:
Business intelligence tools offer greater data analytical solutions. You can collect the data warehouse from various sources. This type of warehousing is more suitable to extract the information to carry out the data analytical task effectively.

Limitations of the Microsoft Power BI:

Below are the few drawbacks of the Microsoft Power BI:

  • This tool is very difficult to implement. You need to loop them in the development team, the IT team to get it executed.
  • To implement row-level security in Power BI and tie your web application users with Power BI users.
  • With users coming and leaving an organization, it becomes a nightmare to manage.
  • Requires considerable investment.
  • You need to buy a premium capacity.
  • Not feasible for pro users.
  • Still users need to visit your web page and the information is not delivered to them.

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Advantages of the Google data studio:

Below are the few benefits of the Google data studio;

It’s a free tool to use:
If you have a Google account, then it’s free to access the tool.

Offers customized report dashboard:
 Google data studio tool allows users to customize the report dashboards with a wide range of text formatting options available such as designs, Styles, graphs, and text headers. If you have new raw data, that will be customized on the dashboard based on your requirement with the help of this pre-built text formatting feature.

Here are some of the things you can format the data:

  • Page layout
  • Text formats 
  • Graphs 
  • Metrics
  • Style element

Offers modern and interactive data visualization:

In Google data studio with the help of a few clicks, you can easily create an engaging and visually appealing dashboard that will attract your audience for sure.

Automated report sharing dashboards:
Google data studio allows you to build an automated report sharing dashboard with the help of real-time data, this process saves your time while reporting.

Offers shareable dashboards:
Google data studio offers a sharing dashboard with the users for multiple tasks. This feature also helps you to communicate among peers and business partners.

You can share the report with the help of these things:

  • Link sharing 
  • Email permissions.
  • Schedules email deliveries.

Limitations of the Google data studio:

Here are the few drawbacks of the Google data studio:

  • Lack of real-time updates with respect to the dashboard.
  • Slow speed in case of live connections.
  • There is no on-premise deployment option available.
  • Lack of native data connectors availability.
  • A limited number of charts per dashboard report
  • Limited interaction with the elements.

Which is the best tool between Power BI and Google data studio?

Here we come to the conclusion part of the article, you can make use of Google data studio sources such as Google data analytics with the data that is readily usable, no need for sharing any complex information. Google data studio tool is a good fit for quick reporting. Most importantly it is a free tool to use unless you need some data connectors.

On the other hand, we have Power BI, this tool is used if you have a wide variety of data transformation options, all you need is a BI tool that has advanced features like greater data transformation capabilities, customization options, and if you don’t mind in paying. Power BI is a powerful robust data visualization and analytical tool, it requires some sort of excel knowledge to perform Power BI dashboards.

You can choose the tool as per your requirements, and data connectivity sources.

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Final thought:

We tried to clear all our audiences’ doubts regarding choosing the best tool between Google data studio and power BI. Both the tools are scalable and robust to use and configure. In this Power BI VS google data studio post, we have mentioned major differences based on the different categories, pros, and cons of the tools.

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