So, I am pretty sure I’m going to get a Macbook. I’ve never had one before but I have an Iphone and an Ipad and I will be starting my Master’s in Research and Data Analysis next year so I want something that fits into an ecosystem so that it’s easy as possible to share files across devices and have multiple workflows going on different devices. This is the only reason why I chose the Macbook over something like a Lenovo laptop.
I need the laptop to be strong enough for Excel, SQL, Tableau, R etc. I may branch out into more coding and other more intensive software as I get more into it. I’m not sure as I’ve only just started on the Data Analysis pathway so I want to make sure the machine I’m getting has room to grow with me as I get more into the field and become a professional. I intend to be using this laptop as my daily driver for everything for the next 5 years minimum.
I think I’m going to go with a Macbook Pro based off Josh’s Youtube buying guide but I just noticed that the M4 Pro chip has two configurations. I wanted to know, for my intended purpose, should I get the higher CPU/GPU config or would the lower one suffice? From what I can see on Amazon, the higher config also comes with 1TB of storage over the 512GB that the lower config comes with. I have 2TB of Icloud storage but I’ve used 1TB storage Windows laptops for a long time now and while I’ve never hit the storage limit, I do photography as a hobby and I worry I may suffer with less space.
I am waiting until Black Friday to see if any exceptional deals show up, especially since the M5 line was just announced but I’d like to know beforehand so I can have a clear idea of what I’m looking for and what I could choose as a backup if the price doesn’t drop into a range that works for me ($1500 - $1700).
I’m pretty sure for data analysis the macbook air would suffice, but the pro is also a great choice, the problem is that the configuration ideal for a data scientist would be very costly lf you go for a pro.
I will not compare AIR and PRO models but I will just state the specs ideal for you. Data science work loads are not cpu intensive but memory intensive. You need to have as much Ram as possible. 32 GB ideal, 24 GB recommended. 1TB SSD is mandatory do not go for 512.
If I may ask, what was your previous laptop? What specs it has and what problems did you face with it?
So, do you think I’d be better off going for an M3 Pro with higher RAM on a discount? If I’m trying to get the power, the RAM, and the price point I want? I ask because I do use Photoshop and Lightroom and my RAW camera files are quite big so the machine needs to handle that as well.
My previous machine is a Dell XPS 7590 with an OLED screen. I just needed a laptop and I got it for cheap on a sale. The worst part about it is the fans! They turn on for EVERYTHING. They have since the day I bought it. The laptop is CONSTANTLY overheating and everything starts slowing down and sticking. And all I did on it for the last 5 years is really basic browsing , undergrad work and entertainment. I only starting using SQL, Tableau, Excel etc in the last 6 months and the computer keeps blue screening now. I upgraded the RAM to 32GB about a year ago and I haven’t noticed a change in performance which I think is because it’s always overheating so much.
No way, do not get a M3 macbook pro. The M5 MacBook Pro just released and the M4 macbook pros will be sold at a very low price in the near future(obviously for clearing up stock). So get the M4 macbook pro with lots of Ram (32 GB).
Although if you do not care about the money I would say to have a look into the newer M5 MacBook Pro. It has 50% better gpu than the M4. I have to say, I’m tempted.
So, for clarification, RAM is more important than GPU core? 32GB of RAM only seems possible with the 10 core CPU/ 10 core GPU on the Macbook Pro M4 chip (not M4 Pro chip). That’s what I’m seeing on B&H. Would that suffice? Also, do you think Thanksgiving would be a good time to wait for M4 Macbook price drops? Or should I hold out until the end of the year if I can?
I’m learning in the field of AI, so I know a bit of two about Data Science.
Excel/Tableau/large R data frames are memory-bound, once data fits in RAM, operations are fast and smooth; when it spills to disk you get long waits. More unified memory = fewer spills to SSD.
SQL clients and local DBs (SQLite, DuckDB) can chew RAM when you do big in-memory joins or analytics.
If you run RStudio + a few R sessions, Docker containers, VS Code + browser tabs, 16 GB will hit limits quickly. 24 GB helps, but 32 GB gives comfortable headroom for heavier multitasking and real-world datasets.
CPU/GPU: M4 Pro’s extra CPU/GPU cores speed compute heavy tasks (parallel R, compiling, some ML libraries, heavy Tableau visualizations). But for pure memory heavy analytics, memory amount matters more than GPU cores.
The M4 base with 32 GB unified memory would be perfect for you, you can even grow with that machine. Although if you can find a deal on the M4 pro MacBook Pro with 32 GB of ram, then get that.
Keep a lookout for deals, black friday is coming; ig that’s the time where the prices of the MacBooks drop. Long story short, buy it when you get a good deal on the macbook.
