Daily, organisations accumulate more and more data from different sources. To make the best use of the data for accurate analysis, it has to be in it's best form.

This piece will unravel how data can be wrangled with Voyance's data engineering infrastructure, Manhattan DB. Let's dive in!

What is Data Wrangling?

Data wrangling is a step further in preparing data after data extraction. This is because the raw data collected could be unusable; in the wrong format and with missing values, making it almost impossible to use. The process of data wrangling helps to sort and unify the data so it can be easily analysed or accessed.

Data wrangling is the process of converting raw data by cleaning, structuring, enriching from formats to another format that is readable, clean and usable by organizations to make decisions. Data wrangling is done to make the data ready for downstream analytics, reporting and machine learning.

In simple terms, it is the process of extracting data from different sources to make it usable.

What is automated data wrangling?

Data wrangling is an indispensable process in data processing which when done manually, takes about 45% time of data professionals. Automated data wrangling is the process of transforming raw data ingested from different sources into usable form using software. Voyance Manhattan DB is an infrastructure software built to carry out data preprocessing tasks like; data consolidation, data cleaning, data wrangling, and overall data transformation

Why should you automate your data wrangling process?

  • Saves time : Data wrangling as a manual process is strenuous. After working round the clock to successfully collect data, merging it together to clean, fill up missing values and transform into a usable form is time draining. The major benefit of automated data wrangling is that it saves time.
  • Improved data usability : Data wrangling provides a better version of the data ingested as the end result. The transformed data can then be used.
  • Accurate data driven decisions : Automated data wrangling beats manual data wrangling in so many ways- by eliminating human errors or bias, the transformed data is accurate for any use at all, decision making, access or analysis.
  • Decentralized access to data : The process of data wrangling, makes it possible for data to be decentralized and easily accessed after getting transformed because the data ingested from different sources is unified before getting wrangled.

Automated Data Wrangling With Voyance Manhattan DB

With Voyance Manhattan DB, you can successfully carry out automated data wrangling in the following steps;

  1. Create a cluster  

A cluster is a combination of virtual machines. By creating a cluster, you are able to choose how many machines you would need for your data pipelining.

While creating your cluster, you can see the estimated cost of your machines per hour, so you can build with a cost in mind.

Voyance Manhattan DB is built with you in mind- to save cost while providing maximum value:

  • Enable autoscaling: This feature permits you to choose a range of machines that would carry out your data pipelining at every point in time based on the computing needs of your data. It helps to save cost so you are not paying for more than the service you enjoy.
  • Terminate: This feature enables you to choose how long after inactivity that you want your cluster to be deactivated. This helps to save cost so your billing does not keep running after inactivity.

2.  Create a project  

Project creation is the main bulk of your work. This is where data ingestion, data cleaning and data transformation as a whole takes place. To successfully create a project after

  • Give your project a name
  • Select your cluster that you created previously
  • Project is successfully created
  • Carry out your data transformation : input your data and carry out your data wrangling . Manhattan DB is built to automate your data wrangling process by helping you fill missing values, organise and in general transform your data.

3.  Create job to automate the entire pipelining process

Who can benefit from the use of Automated Data Wrangling process with Manhattan DB?

  1. Sales department

With Voyance Manhattan DB, sales department can automatically ingest data from customers’ ID, sales invoices, financial records, and other necessary records to be able to track sales for a given period of time and then make further decisions with the wrangled data.

2.  E-commerce firms

Data ingested from different sources like products, customers, stores, sales, purchases, and pricing could be unified and transformed for further use.

3.  Consultancy firms

By ingesting data from past experiences with clients, consultancy firms can make data based decisions with Manhattan DB which will transform the data for further analysis or use.

4.  Fintechs

Manhattan DB can be used to ingest data from different sources like financial records, user activity on the website or app, customer identity information and to clean the data, fill missing values and in general, pre-process it before sending it can be used for anything else.

5.  Internal firm’s report strategy

Usually, various departments have different sources of data due to their methods of operation. At the time of reporting there would be data conflicts owing to the fact that the data is ingested manually.

With Manhattan DB, a firm’s internal report can be ingested from various departments and then cleaned and stored. The data processed would be made accessible to everyone, hence boosting data efficiency.

6.  Energy firms

Energy firms can use Manhattan DB to understand consumption patterns and improve network performance through an aggregate of data collected and wrangled.

7.  Schools

Educational institutions like universities which have many end users, can use Manhattan DB to ingest data from various departments in the organization. That way, every head of department can easily access data without running around. This would also give room for faster decision making as well.

8.  HR department

The HR department in a large firm will find Manhattan DB useful to quickly ingest staff data from different departments and ascertain their working capacity within a certain period. This also helps the HR person to be more efficient.

Automated data wrangling makes wrangling seamless and much easier. Get in touch today so you can be eased off the stress of wrangling data manually.