Data solutions for no-code problems 🌐
Tools like Bright Data’s ‘Data Collector’ are leading the way with solutions.
The biggest ‘No Code’ issues today, fixed by Bright Data
#1: Dealing with unstructured data ⛔
Unstructured data files include:
Duplicate/incomplete data points
Incorrectly formatted or mislabeled datasets.
They come in a variety of formats and require a lot of time and manpower to structure, and prepare for analysis.
#2: Finding ways to collect qualitative data 🤯
Qualitative data gives you context, and a clear narrative of what is going on in your industry, such as: How do consumers feel about a brand or product on social media? (i.e. social sentiment data). But navigating social media site architectures can be complex.
Automating E[xtract] T[ransform] L[oad] pipelines 🚀
Creating ETL data extraction pipelines are a crucial part of decreasing a company’s ‘time to insight’. A good ETL data ingestion flow will enable companies to collect raw data in various formats, from multiple sources, and input it into their systems efficiently for analysis. This is a lengthy, manual process which can set a project back days, weeks, or even months.
Data-on-Demand addresses these issues within the framework of the ‘no-code’ community.
Data that is cleaned, parsed, and structured automatically and delivered in a single format of your choice (JSON, CSV, HTML, or Microsoft Excel) directly to algorithms and team members.
It uses Machine Learning (ML), and Artificial Intelligence (AI)-based algorithms and retry logic in order to circumvent complex target site architectures, delivering target data points within minutes, at the click of a button.