2022 Raw data Assignment help

What is raw data?

Raw data, sometimes called atomic data or primary data, is the original form that the information takes. This is not yet processed for use, meaning that it can’t be understood by you or other processes right away. Data is sometimes classified into data that has undergone data processing and raw data. The end product of processed data, which is also referred to as cooked data, is often called information. Assignmentsguru.com is the best place to find help for your Raw data assignments. We have A pool of experienced writers from all over the continent who can provide you quality assignment.

Although raw data has the potential to become “information,” it requires selective extraction, organization and sometimes analysis and formatting for presentation. It is  possible  to process and analyze data in various ways as long as they are stored in a distributed database.

How raw data works

Tremendous amounts of raw data surround us and are produced every day. The human brain is incredibly good at taking in raw data, processing it and using it to make decisions.

For example, imagine you are trying to cross a busy road. The eyes capture raw data as flashes of light and dark. Then the brain takes these flashes and resolves them into objects such as street signs and cars. The working memory can tell you if that car is sitting still, getting bigger as it comes toward you, or getting smaller as it drives away. Meanwhile, the ears take in raw information in the form of vibrations in the air, which the brain translates into sounds that can be interpreted as the wind, voices or a car engine. Finally, all this processed data that came in through the eyes, ears and memory helps you make the informed decision to cross the street or not.

This is not necessarily true. Computers are able to process raw data quickly and they don’t need a lot of processing done in order for it to be useful. Additionally, a system that processes raw data over and over again may only provide the same result each time without any thought put into what exactly it is producing.

For example, imagine a simple home thermostat. Its raw data source is a temperature probe — usually read as an analog voltage level. The system takes this voltage level as raw data and turns it into a temperature reading. It can then use this processed data to meet a predetermined desired temperature for turning on and off a heater or air conditioner.

Furthermore, the system may feed this temperature reading and the current time into another climate control system as that system’s raw data. Then the data that is generated during your heating or cooling systems is analyzed to provide future insight into how the system will perform based on past failure rates. This provides a predictive modeling algorithm to help make better decisions for your customers

How to process raw data

Many sources can produce raw data. How it is processed and stored depend on its source and intended use, though. Raw data can be anything from financial transaction records to eye tracking software. It allows companies to get the most information possible on how they are running their business, what works & what’s not & even how they can improve upon these areas of their company. Data exchange between systems is most often accomplished with comma separated values files. These files are easily readable by just about any system through text-based file formats like CSV (Comma Separated Values).

In many instances, users must clean raw data before it can be used. Cleaning raw data may require parsing the data for easier ingestion into a computer, removing outliers or spurious results and, occasionally, reformatting or translating the data — a process sometimes called massaging or crunching the data.

There are many ways to process data, ranging from simple to complex. One example of a simple table that can be created in Microsoft Excel or Google Sheets is shown below. This tool allows users to organize, format, and graph data for quick insights about a particular topic. Maybe your company is looking to use it for insight purposes but may use raw data from a business intelligence program to make adjustments on the fly. Some advanced systems are able to use raw data for information purposes or to build models with machine learning.

Value of raw data

The primary value in data is after it has been processed and interpreted. There is generally not much value in holding onto raw data without a way to use it, but as the cost of storage decreases, organizations are finding more and more value in collecting raw data for additional processing — if not right away, then later.

Raw data may contain personally identifiable information (PII). Organizations may use data anonymization to remove PII from the raw data or implement data retention policies to limit the risk of data leaks.

Organizations use data warehousing to collect and store data in a centralized location. Data warehousing often uses skills like correlating and processing in order to make sense of the information gathered. It’s important to note: There is no one single source for data warehouse software, but all can be used in different ways. An analysist can then query the data using BI tools to produce useful information from the data.

Many large businesses today recognize the value of raw data. Consumer data is a hot commodity that they can buy and sell to build profiles of users or target a specific audience, for example. Businesses can also store operational and logging data for use in performance metrics and to streamline business practices, while they can use access logs and the like to identify computer breaches and track what data may have been accessed by hackers.

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