In this digital world, we are surrounded by a massive amount of data. If you are using the internet, you are generating data in some form or the other. Companies are collecting this unprecedented amount of data to gain better customer insights and make more informed business decisions. However, the data generated at the source is in raw format and needs to be processed and analyzed before we can draw conclusions from them. You must have come across data in formats like text, images, GIFs, or videos. The other forms of data are generated through electronic devices or sensors, medical equipment, social media platforms, and so on. Such unstructured data needs to be gathered first from different sources and then taken for further process of data science.
Now, data collection and its preparation isn’t an easy task; a company requires proper tools and techniques to handle big data. Apart from data collection, there are various tools for the entire data science life cycle. Knowledge of these tools is essential if you are preparing for any data-related job role. In fact, all the data engineering courses in India make you familiar with some of the top data science tools used by enterprises.
This article particularly focuses on the top data collection tools that you should know about.
Top Data Collection Tools
Described below are some of the top data collection tools that you may be interested in:
Datameer Spectrum
Datameer Spectrum is a powerful tool that combines the full power and reliability of fully-featured ETL (extract, transform, and load) to transform your data from raw form into analysis-ready in a short amount of time without one line of code. It facilitates a consistent data flow through complete operationalization and governance features that result in reliable, secure, and automated data pipelines. The tool supports the largest number of data sources and destinations, data formats, and has the wealthiest wizard-driven function library in the industry to tame any data.
SAP Data Intelligence
You can describe SAP data intelligence as a comprehensive data management solution. It transforms distributed data sprawls into essential data insights and delivers innovation at scale. The tool supports end-to-end data orchestration, including ETL, event processing, data quality, data catalogs, workflows, and scheduling. By detecting patterns, it can collect data from various sources and perform a detailed analysis of source data. It tries to understand the structure, quality, and content of source data and its relationship with other data. SAP data intelligence also facilitates creating data pipelines with a variety of connectors and built-in adapters.
Trifacta Wrangler
An open and interactive cloud platform, Trifacta is ideal for data analysts and engineers to profile, prepare, and pipeline data for analytics and machine learning. Anyone who has worked with Excel or Tableau can have an intuitive data wrangling experience with Trifacta and they can explore and prepare data for analysis efficiently. The tool offers an AI-assisted self-service approach, democratizes data and facilitates assessment, correction, and validation of data quality to accelerate transformation, and automate robust data pipelines at scale. Trifacta is ranked 4.5 out of 5 by users in Gartner Peer Insights for data preparation tools.
Alteryx APA Platform
The Alteryx Analytic Process Automation (APA) Platform is another popular tool that delivers end-to-end automation of data science processes and analytics. It supports over 80 natively integrated data sources from Amazon, Oracle, to Salesforce. You can securely connect to an unlimited number of additional sources. If you can access the data, you can bring it into this tool and spend more analyzing rather than searching the data. The platform allows users to easily cleanse, prepare, and blend data from a variety of different sources to deliver unified data profiles.
Tableau Desktop
Tableau is a leading data analytics platform that supports data cleaning, data processing, and visualizations as well. You can connect to data on premises or in the cloud, be it big data, spreadsheet, SQL database, or cloud applications like Salesforce and Google Analytics. There is no need to write code for accessing and combining disparate data. Power users can split, pivot, and manage metadata to optimize data sources. You can extract massive data for limitless exploration in seconds. The tool has built-in data cleaning and preparation capabilities that help users connect to data and get more accurate answers.
Microsoft Power Query
Power Query is a convenient way to connect, extract, transform, and load data from a wide range of sources. Its powerful data connectivity and preparation feature helps users access data stored in hundreds of sources seamlessly and reshape it to fit their needs. There are built-in connectors and generic interfaces along with the Power Query SDK to build your own connector. No coding is needed to start connecting, cleaning, transforming, and combining data. Power Query seamlessly integrates with many popular Microsoft products like Power BI.
With so many powerful tools available, which one are you going to explore? Working knowledge of any of these tools is beneficial for data-related interviews. You can also take up a data engineering course to learn more about these tools.
