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Best Data Automation practices for Start-ups | PromptCloud
 

Best Data Automation practices for Start-ups

Best Data Automation practices for Start-ups

Big Data automation is considered as one of the major enabling forces to help simplify business processes by enabling smooth flow of information and reducing operational costs. Big Data Automation is going to transform entire organizational set-up across businesses worldwide. Today, business processes are being analyzed for gaps and potential optimization areas throughout the business world. Automation of Big Data is sure to help businesses store, process and enrich data faster and better.

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In the world of Big Data, human insufficiency and restricted budget may prove a hindrance in leveraging data for different purposes. Some of the reasons why we need Big Data include countering competition, improving decision-making, devising better workflow of operations, and boosting profitability. Big Data automation will transform the way in which virtual and cloud environments are managed. On bringing virtualization and the cloud into the automation platform, assigning resources to workload processing as per the requirement and then returning those resources when the workload is complete will be easier.

Data integration automation enhances business intelligence capabilities by offering simple, secure, process automation solutions. These solutions can offer high speed extraction of data, metadata and others as well. These solutions help to automate, incorporate, manage and support in a cost effective manner. IT automation is going to act as a driving agent triggering off efficiency and significantly reducing the cost of operations. It has been delivering services for years with automation being the focus of IT automation services.  Its value will really become evident in near future. It will significantly bring down the cost of IT operations by driving efficiency through automation of resource-intensive and time-consuming processes. IT automation has been delivering productive results since 2012 but with focus shifting towards automation and its widespread adoption, its value will become more evident.

IT automation is the future. It is going to automate big data along with data integration. Start-ups as well as large enterprises are relying on data to enhance decision making. With volume of data increasing, the number of distinct data sources offering feed to data warehouses is increasing strikingly. Data Automation is going to emerge as a key player in automating and integrating the movement of data between these distinct sources to improve data quality.

Here’s a list of Best Data Automation practices for Start-ups:

  • Selecting the right tool for Automation:

data centre automationSelecting the right tool for Automation is just the start. Some people may misread that if they select a right tool, they can easily automate anything. Automation tools make the data automation process easier but you need to have right skills to carry out the automation process flawlessly. The automation tool used for the application should be in synchronization with the application. For instance, if your application that needs to be tested is developed in ASP.NET then the resources should be familiar with ASP.Net.

  • Hiring Skilled Automation expert:

At times, automation tools can be a real problem in identifying complex objects on the application. This suggests that selecting the right tool is not enough unless there is a skilled automation expert to unleash the full potential of these tools. Hiring an adept automation engineer along with selection of right tool will help in bringing about automation in a seamless manner.

  • Relying on automation tool:

An automation tool is important but you should not rely too much on a tool. Some professionals may believe that just by choosing a good tool, they can easily automate anything. But, that’s not true. You need skilled professionals to complete the process. Tools cannot ensure success without being administered by adept professionals.

  • Understanding the application and related technology:

Understanding the application along with technology used is highly significant aspect of automation. Deeply analyzing the product before starting the automation is recommended by professionals. For instance; if you are using a web application, you should have an in-depth knowledge of browsers it will support. On using a desktop application, you should have a fair knowledge of language that it is built upon.

  • Automating everything is not possible:

Automation helps in saving time for testing professionals by helping them to concentrate on other important aspects of work. Automation cannot replace the testing workforce completely. It might just help minimize the workload of testing team by executing the recurring and repeatable processes for them. This allows them to prioritize tasks and focus on finding bugs or creating newer test scenarios.

Data scientists are aware of the fact that trusting machines alone is not enough. Analyzing this situation cleverly, companies have figured out how to automate work without replacing professionals. Big Data technologies can analyze a vast volume of data, which isn’t even practically possible for humans to achieve in a stipulated time frame. Big Data specialists begin their work once the machines have done their bit and it is time for some human judgement. These professionals use their expertise to uncover insights and add perspective to final algorithms. Start-ups are leveraging automation technologies along with Big Data specialties to enhance their success rate.

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