10 Best laptops for data analysis in 2023

As a laptop enthusiast with a keen interest in data analysis, I understand how crucial it is to find the best laptop for data analysis tailored to your specific needs. The right laptop can significantly impact your productivity, efficiency, and overall job satisfaction. As such, I have reviewed an extensive laptop spreadsheet of recent releases, comparing specs and reviews from professional sources and user-generated content, to help narrow down the top laptops based on the unique requirements of data analysts and various price ranges.

When choosing the best laptop for data analysis, there are several key factors to consider, such as processing power, RAM capacity, storage options, and display quality. Data analysts often work with large datasets and resource-intensive applications like Excel, Python, R, or Tableau. A powerful processor, such as an Intel Core i7 or AMD Ryzen 7, coupled with at least 16GB of RAM, will ensure smooth multitasking and seamless data processing. Additionally, having a fast SSD and a high-resolution display will enhance your overall experience, especially when working with intricate visualizations or data models.

In my quest to find the best laptop for data analysts, I have also taken into account the preferences and recommendations of professionals within the industry. For instance, I have consulted popular data analysis forums, subreddits, and online communities to gather insights on what real-world users value most in their laptops. By combining these findings with my knowledge of the latest laptop technologies, I am confident that this guide will provide valuable assistance in your search for the perfect data analysis laptop.

Processing power: The backbone of your data analysis laptop

Data analysis is a demanding task that requires a powerful processor to handle large datasets and complex algorithms. When choosing a laptop processor for data analysis, it's important to consider factors such as performance, battery life, and price. Here's what you need to know about the latest processors on the market and how to choose the right one for your needs.

What's new in the processor market?

Apple has recently released MacBooks with ARM-based M1, M2, M2 Pro, and M2 Max system-on-chip modules. These processors offer exceptional single-core performance and battery life, making them a great choice for data analysis. AMD has also captured 20% of the laptop CPU market with its 6th and 7th-generation Ryzen processors, which offer competitive performance at a lower price point. Intel's 13th-generation Core processors have already been released, but the 12th-generation Core CPUs can still provide excellent value.

How much CPU power is needed for data analysis?

The amount of CPU power needed for data analysis depends on the size and complexity of the datasets you're working with. For most users, a quad-core processor with a clock speed of at least 2.5 GHz will be sufficient. However, if you're working with very large datasets or running complex algorithms, you may need a higher-end processor with more cores and a faster clock speed.

Macs vs PCs for data analysis

Data analysis can be done on any platform, but Windows laptops are more popular than MacBooks because they're more affordable and offer similar performance. MacBooks are a great choice if you prefer macOS or need to use software that's only available on macOS.

Which processors are best for data analysis?

If you're looking for a top-notch laptop for data analysis, look for an H-series processor, such as an i9 or Ryzen 9. These processors are designed to handle demanding tasks such as data analysis and machine learning, but they come at the cost of battery life. Ryzen models are best if you need a good battery life in a PC laptop.

When comparing processors, use PassMark and Cinebench R23 to compare different processors across various price points. These benchmarks test the entire system instead of just one component, giving you a more accurate picture of overall performance.

Recommended processors

Here are our recommendations for the best processors for data analysis at different price points:

Price Range Processor Cores/Threads Base Clock Speed Boost Clock Speed TDP
Under $700 AMD Ryzen 5 5500U 6/12 2.1 GHz 4.0 GHz 15W
$700-$1000 AMD Ryzen 5 5600U 6/12 2.3 GHz 4.2 GHz 15W
$1000 and up Intel Core i5-11500H 6/12 2.5 GHz 4.6 GHz 45W

Note that these are just recommendations; the best processor for you will depend on your specific needs and budget. By considering factors such as performance, battery life, and price, you can find the right processor to handle all your data analysis needs.

Graphically Speaking: Finding the Perfect GPU for Data Analysis


When it comes to data analysis laptops, the GPU is not the most critical component to consider. In fact, if you're using a MacBook, the integrated GPU is more than enough for most data analysis tasks. However, if you're looking for a Windows laptop, the GPU plays a more important role.

If you're not using your laptop for gaming or other demanding tasks, you can get by with a mid-range graphics card. Nvidia's latest generation of GPUs, RTX, offers some exciting new features that can improve data analysis performance, but these features are not yet widely supported by data analysis tools and libraries. Therefore, I recommend focusing on traditional performance benchmarks such as 3DMark and Cinebench R23 to determine the best laptop graphics card for your needs.

When comparing graphics cards, I use 3DMark scores because they provide an apples-to-apples comparison of laptop GPUs. However, some people might prefer more general benchmarks such as Cinebench R23 or PassMark Gpu test since these offer a more complete picture of overall performance.

It's worth noting that the gap between power-limited notebook graphics and desktop graphics cards has widened in recent years. Desktop GPUs are now more power-hungry, and Nvidia has discontinued the Max-Q label for its RTX graphics cards. Now, the exact GPU wattage is determined by a laptop manufacturer, which can result in a wide variance in graphics performance even in laptops with the same GPU chipset.

If you're looking for a high-end gaming laptop with a fast processor and plenty of RAM, make sure it has an Nvidia G-Sync panel instead of an AMD FreeSync panel. G-Sync is superior in terms of input lag reduction and visual quality preservation when framerates dip below the refresh rate (which is common in games).

Based on my experience, here are my recommendations for laptop GPUs at different price brackets:

Price Bracket GPU Recommendation
Minimum GeForce GTX 1650
Recommended GeForce RTX 3050
High-end GeForce RTX 2060

Keep in mind that these are general recommendations, and your specific needs may vary. Ultimately, the most critical factor in choosing a laptop GPU for data analysis is to ensure that it meets your specific performance requirements without breaking the bank.

RAM up your data analysis game


RAM is an essential component in any data analysis laptop. While the CPU and GPU are critical, the amount of RAM you have can make a significant difference in some cases.

Most mid-range laptops come with 16 GB of RAM, which is sufficient for most tasks. However, if you work with large datasets, such as those over 1 TB, we recommend looking for a laptop with at least 32 GB of RAM. If you need even more memory, a desktop replacement laptop that supports DDR5 memory and has at least four memory slots may be a good option.

When it comes to memory types, the latest-gen Intel and AMD CPUs support DDR4 and DDR5. While DDR5 is faster and more efficient, it's still relatively expensive and needs time to mature as a technology. Therefore, DDR4 is currently the most common and cost-effective option for laptops.

Latency and frequency are also important considerations when choosing RAM. Latency refers to the time it takes for the RAM to respond to a request, while frequency refers to the speed at which the RAM can transfer data. Generally, lower latency and higher frequency are better, but the difference in performance can be minimal for most data analysis tasks.

In summary, we recommend at least 16 GB of RAM for data analysis laptops, but 32 GB is ideal for larger datasets. DDR4 is currently the most cost-effective option, and other factors such as latency and frequency are not as crucial for most tasks. Below is a table of our recommendations for different price ranges:

Price Range Recommended RAM
Budget ($500-$800) 16 GB DDR4
Mid-Range ($800-$1500) 32 GB DDR4
High-End ($1500+) 64 GB DDR4

Data Analysis Laptop Buying: Your Questions Answered

Q: What are the best laptops for data analysis?

The best laptops for data analysis are the ones with high processing power and large memory. Some great options in the market include HP Victus 15t, Lenovo Legion 5 Pro, GIGABYTE AORUS 15 XE4, ASUS ROG Strix Scar, and ASUS ROG Zephyrus Duo.

What specs do I need in a laptop for data analysis?

To perform data analysis on a laptop, you need a laptop with a powerful processor, large memory, and a good graphics card. The recommended processor is either AMD Ryzen 5 5600U or i5-11500H, a minimum of 16 GB of RAM, and at least a GeForce GTX 1650 graphics card.

How much RAM do I need for data analysis on a laptop?

It is recommended to have at least 16 GB of RAM to perform data analysis on a laptop. However, for large datasets, it is advisable to have 32 GB or 64 GB of RAM for optimal performance.

What is the best processor for data analysis on a laptop?

The best processors for data analysis on a laptop are either AMD Ryzen 5 5600U or i5-11500H, both having excellent multi-core performance.

What are the minimum requirements for a laptop for data analysis?

The minimum requirements for a laptop for data analysis are an i5-11320H processor, 16 GB of RAM, and at least a GeForce GTX 1650 graphics card.

Can I use a gaming laptop for data analysis?

Yes, you can use a gaming laptop for data analysis as it provides high processing power and large memory. However, gaming laptops are usually heavier and thicker, making them less portable than regular laptops.

How to choose a laptop for data analysis?

When choosing a laptop for data analysis, you should prioritize high processing power and large memory. Check the recommended requirements mentioned above and select a laptop within your budget. Also, ensure that the laptop has a good cooling system to avoid overheating during prolonged usage.

Is SSD necessary for data analysis on a laptop?

SSD is not necessary for data analysis on a laptop, but it significantly improves the performance and speed of the data analysis process.

Can I use a MacBook for data analysis?

Yes, you can use a MacBook for data analysis, but it is recommended to have at least 16 GB of RAM and an SSD for optimal performance. Additionally, some software used for data analysis may not be compatible with macOS, so it is advisable to check for compatibility before purchasing a MacBook.

How much storage do I need for data analysis on a laptop?

The storage required for data analysis on a laptop depends on the size of the datasets being used. However, it is recommended to have at least 512 GB of storage space. If you work with large datasets, you may need a 1 TB or larger SSD.

5 Best Laptops for Data Analysis

i5-12450H | GTX 1650 | 32 GB RAM | 2000 GB SSD | 15.6″ IPS WA; 1920x1080 |

1.HP Victus 15

HP Victus 15 is a budget-friendly laptop suitable for basic data analysis tasks.
  • Excellent price
  • Good gaming performance
  • Suitable for basic data analysis tasks
  • Poor battery life
  • Plain design

The HP Victus 15 is an affordable gaming laptop that can handle high-end games and basic data analysis tasks with ease. While it's not recommended for those who need a longer battery life or a more sophisticated appearance, it's an excellent choice for budget-conscious users.

HP Victus 15
Lenovo Ideapad3i
  • Reasonable productivity and 1080p gaming performance
  • Good battery life
  • Dark display
  • Poor keyboard
Ryzen 7 6800H | RTX 3060 | 32 GB RAM | 2000 GB SSD | 16″ IPS HDR G-Sync; 2560x1600 |

2.Lenovo Legion 5 Pro

Lenovo Legion 5 Pro is a powerful laptop with a high quality display, but its battery life and lack of Thunderbolt support may be a drawback.
  • High quality 165 Hz 16:10 IPS display
  • Relatively easy serviceability
  • Integrated numpad
  • Very fast charging
  • Low resolution webcam with no IR or privacy shutter
  • Very warm CPUGPU temperatures when gaming
  • Moderate-heavy uneven backlight bleeding
  • Only average battery life

With a 150 W TGP GeForce RTX 3070 Ti and upgraded AMD Zen 3+ CPU, the Lenovo Legion 5 Pro is faster than its predecessor. Its high quality 165 Hz 16:10 IPS display and easy serviceability make it a great option for data analysis, but it lacks Thunderbolt support and has only average battery life.

  • Fast GeForce RTX 3060
  • High refresh rate IPS panel with full sRGB coverage
  • Chassis base and lid have some flexing
  • No per-key RGB lighting
i7-12700H | RTX 3070 Ti | 64 GB RAM | 2000 GB SSD | 15.6″ IPS-level; 2560x1440 |


The GIGABYTE AORUS 15 XE4 is a powerful and efficient laptop for data analysis with a stunning display and impressive storage options.
  • Impressive performance
  • Stunning display
  • Impressive storage options
  • Efficient power delivery
  • High power usage at idle and low load
  • No card reader
  • Only one USB-A port

The GIGABYTE AORUS 15 XE4 is an energy-efficient laptop that packs a punch with its impressive performance, a 165Hz panel, wide color gamut, and a PCIe 4.0 SSD. It also comes with a free M.2 2280 slot and Thunderbolt 4 with power delivery.

ASUS ROG Strix G15 G513RM
  • Punchy and fast QHD 240 Hz screen
  • Good inputs and IO
  • Some quirks affecting everyday ergonomics
  • No ThunderboltUSB 4, card-reader, camera or biometrics
Ryzen 9 5900HX | RTX 3080 | 64 GB RAM | 4000 GB SSD | 15.6″ IPS-level G-Sync; 1920x1080 |

4.ASUS ROG Strix Scar

ASUS ROG Strix Scar is a powerful laptop for data analysis but struggles with heat and noise emissions.
  • Sturdy construction
  • Fast Wi-Fi 6E
  • Wide color gamut coverage with Dolby Vision support
  • Unhindered Core i9-12900H and RTX 3070 Ti performance
  • Limited display angle
  • Heavy SSD throttling during continuous reads
  • High heat and noise emissions under load
  • Battery backup could have been better

The ASUS ROG Strix Scar 15 G533 is a powerful laptop with impressive specs that can cater to the needs of enthusiast gamers as well as data analysts. The laptop's construction is sturdy, has fast Wi-Fi 6E, no PWM, and a wide color gamut coverage with Dolby Vision support. However, the laptop struggles with high heat and noise emissions under load.

Acer Predator Triton 500
  • High-performance capabilities
  • Excellent 240-Hz display
  • Soldered-in RAM
  • Inaccessible SSD
Ryzen 9 6900HX | RTX 3070 | 32 GB RAM | 1000 GB SSD | 16″ IPS mini-LED HDR Touch; 2560x1600 |

5.ASUS ROG Zephyrus Duo

ASUS ROG Zephyrus Duo is an expensive but powerful choice for data analysis.
  • Impressively thin, elegant design considering dual displays and sheer power
  • Refined two-screen layout
  • Blistering gaming performance with a GeForce RTX 3080 Ti GPU, Ryzen 9 CPU
  • Eye-watering cost, especially as configured
  • Awkward keyboard and touchpad layout
  • Poor battery life

The ASUS ROG Zephyrus Duo is a laptop with an elegant dual-screen design, top-end performance, and a GeForce RTX 3080 Ti GPU, making it an impressive choice for deep-pocketed data analysis enthusiasts.

ASUS ROG Strix Scar G733CX-XS97
  • Good QHD panel with 240 Hz
  • High and stable gaming performance
  • Inconsistent SSD performance
  • Additional premium for HX CPU isnt worth it

Table of the Best Laptops for Data Analysis

LaptopPrice (approx)
HP Victus 15$880
Lenovo Legion 5 Pro$1,350
ASUS ROG Strix Scar$2,310
ASUS ROG Zephyrus Duo$3,170
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John Winstler
With over a decade of experience in the tech industry, combined with a degree in computer science, I have developed an in-depth knowledge of laptops, PC games, software, 3D modeling, video editing, and photo editing. My detailed and unbiased laptop reviews have helped many people make informed decisions about their technology purchases.

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