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Row Zero is a last-mile analytics tool that enables operations, finance, marketing, and other business teams to analyze and work with big data sets in a familiar and flexible spreadsheet designed for big data. Row Zero can open 1 billion row data sets, connect directly to data warehouses, and support multi-user collaboration to make working with hosted data easy for anyone with spreadsheet skills. Row Zero closes the last-mile analysis gap helping business teams take insights from dashboards and turn them into actionable results.
Row Zero Features
Speed and Performance - Row Zero has adapted state-of-the-art columnar analytics techniques to a spreadsheet interface and leverages cloud computing strategies to enable users to import, open, and interact, cell-by-cell, with 1 billion row data sets, like they would in Excel and Google Sheets.
Connectivity - Row Zero’s native connections to data warehouses provide efficiency gains for business teams who, instead of building one-off static analyses, like financial models and demand forecasts, can build them once using a connected table and schedule automated refresh.
Collaboration - In order for data analysis to be valuable the work must be shared across teams, business units, and organizations. For this reason, Row Zero workbooks can be shared with viewer and editor permissions and support real-time collaboration for group work and facilitating efficient presentations.
Governance – Row Zero runs in the cloud, enables sharing permissions (viewer and editor), and enforces data permissions from the data warehouses, eliminating the need to email .xlsx files. Security - Row Zero is SOC2 Type II certified and HIPAA compliant. The SOC II report and a BAA are available upon request.
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RowZero.io's answer:
Row Zero's is a last mile analytics tool that enables business teams (marketing, operations, finance, etc...) to connect to cloud data warehouses and work with big data sets in a spreadsheet they already know how to use. BI tools are great for high level metric monitoring but the work initiated as a result of those dashboards needs to happen in a tool where business teams can see and interact with their data.
RowZero.io's answer:
Row Zero is the world's fastest spreadsheet, designed for big data sets. If a user already knows how to use a spreadsheet and needs to analyze or transform large data sets, Row Zero is the perfect tool. Data teams that serve large businesses can off-load ad-hoc and last mile analytics requests by enabling their business partners to work in Row Zero.
Based on our record, Packer should be more popular than RowZero.io. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you have just upgraded to Ubuntu 22.04, and you suddenly experience either errors when trying to ssh into hosts, or when running ansible or again when running the ansible provisioner building a packer image, this is probably going to be useful for you. - Source: dev.to / over 1 year ago
I am already using Hashicorp Packer at work and for personal projects and I wanted to test This idea out by wrapping it a single Packer Template file. This reduces the level of maintaining a lot of small scripts, Dockerfiles and configurations and the user can simply trigger a couple of Commands to get a minimalist OS at the end of the process. - Source: dev.to / almost 2 years ago
And while it is a slight increase in complexity, it can be an overall net gain in functionality, configurability and reliability. Much like Packer is far more reliable and practical than manually making VM images sitting in front of a terminal, even though making the initial configuration takes some time. Source: almost 2 years ago
Hashicorp Packer provides a nice wrapper / abstraction over the QEMU in order to boot the image and use it to set it up on first-boot. Instead of writing really long commands in order to boot up the image using QEMU, Packer provided a nice Configuration Template in a more Readable fashion. - Source: dev.to / almost 2 years ago
Packer seemed like the perfect tool for the job. I have never used it before and wanted to get familiar with the tool. It doesn't come with ARM support out of the box, but there are two community projects to fill that niche. - Source: dev.to / about 2 years ago
We built our spreadsheet (https://rowzero.io) from the ground up to integrate natively with Python. Bolting it on like Microsoft did, or as an add in like xlwings, just feels second class. To make it first class, we had to solve three hard problems: 1. Sandboxing and dependencies. Python is extremely unsafe to share, so you need to sandbox execution. There's also the environment/package management problem (does... - Source: Hacker News / 17 days ago
I think calling out Durability is a bit of a straw man. Most services get their durability from S3 or some other managed database service. I agree with the other points for production services with the caveat that many workloads don't need all of those. Internal workloads or batch data processing use cases don't need 4 9's of availability. "Just do it on a beefy machine" is part of our thesis for... - Source: Hacker News / 25 days ago
If you like spreadsheets, check out https://rowzero.io. It looks and feels like Google Sheets and scales to 1B+ row data sets. We natively support Python and Parquet, and connect directly to Postgres, Snowflake, Databricks, Redshift, and S3. - Source: Hacker News / about 1 month ago
Shameless plug: If you have bigger data sets, check out https://rowzero.io We scale up to hundreds of millions of rows and have native Python support. You can define functions in Python and call them as formulas from any spreadsheet cell. We seamlessly marshal Pandas dataframes from Python land to spreadsheet land and back. [1] We're also hosted and support real time collaboration like Google Sheets. We... - Source: Hacker News / about 2 months ago
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