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:

  1. Duplicate/incomplete data points

  2. Corrupted files

  3. 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

Data-on-Demand addresses these issues within the framework of the ‘no-code’ community.

Tools like Bright Data’s ‘Data Collector are leading the way with a solution that offers:

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.

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