Starting with a data analytics project comes with innumerable questions. What are the goals of the project? What should you know about your data? And where do you start?
As you start with the project, it’s important to understand all the elements that ensure efficiency and the best business results. Data analysis is an important part of the data science domain. It follows a rigorous process to complete the project. Each stage needs different skills and knowledge. Understanding the whole process is important to gain meaningful insights.
In this blog, we will explore the crucial steps in data analysis. It will cover how to define the goal, collect relevant data and analyze efficiently. This will help you tweak the process which fits your requirements and project needs.
The first step towards a successful data analytics project is understanding the company or business where the data project is embedded. The data analytics project should be the answer to a clear and precise organizational need that inspires the various actors involved in bringing it from idea to deployment.
Talk to the individuals in the organization whose processes are required to improve with the data. Then decide on a timeframe and reach specific critical performance metrics. While working on a personal project or experimenting with a dataset, this step may seem useless, but it is not!
It is not enough to download a cool open dataset without having a clear objective of what you want to do with the data. To have motivation, direction, and purpose to work on the project, a specific question must be answered, a problem must be solved.
Related Read: Understand The Importance Of Data Analytics And Its Future
After working out the purpose, the next step is looking for data. What makes a data project amazing is blending and uniting data from as many data sources as possible. Here are a few options for obtaining usable data:
To connect to a database: Request data from your data and IT departments, or open your private database and begin digging through it to see what information the firm has been collecting.
APIs: Consider APIs for all of the tools the company has been utilizing and the data collected by respective people. You can set these up and leverage the database open to enter statistics and other data.
Look for open data: The Internet is full of datasets that can be used to supplement what you already have.
Caution! The following phase is the most feared step in the data analytics project, which can consume most of the time spent on the project. Now that the data has been obtained, it is time to investigate and clean it up. Look through what is collected and how it can be connected to attain your goal. Analyze and understand the variables, and ask around other members of the organization.
Cleaning is the next stage; examine each column to ensure that the data is homogeneous. This is undoubtedly the most time-consuming and aggravating part of your data analytics endeavor. It may be difficult for a while, but one should be focused on the end objective. Finally, one critical aspect of data preparation that should not be overlooked is ensuring that the data and the project align with the data privacy rules.
Personal data privacy and protection are becoming top priorities for users, businesses, and legislators. To execute privacy-compliance initiatives, consolidate your data efforts, sources, and datasets into a single location or tool. For datasets and projects that contain personal or sensitive data, designate them and treat them accordingly.
Once clean data is obtained, one can start manipulating it to extract the most value out of it. To begin the data enrichment portion of the project, you should combine all of the diverse sources and group logs to limit the data to the most important attributes.
One way to do this is to create time-based characteristics in the data that dates, holidays or months can break down. Uniting datasets is another technique to enrich data. It is about picking columns from one dataset or tab and putting them into a reference dataset.
This is an important part of any study, but it can rapidly become a nightmare if you have many of them. The key is to be extra cautious while collecting, preparing, and altering the data to avoid accidental bias or other undesirable trends.
Sandeep is a certified, highly accurate, and experienced Data Scientist adept at collecting, analyzing, and interpreting large datasets, developing new forecasting models, and performing data management tasks. Sandeep possesses extensive analytical skills, strong attention to detail, and a significant ability to work in team environments.
Get Free ConsultationFinally, a decent dataset has been obtained! Visualization is the best way to examine, study and convey discoveries when dealing with large amounts of data. The tough aspect is being able to go into your graphs at any time and respond to any query someone could have about a certain insight.
Another technique to expand data collection and produce more intriguing characteristics is to use graphs to produce specific results and observations.
Phase six is where the real fun begins! Machine learning algorithms can assist in gaining additional insights and forecasting future trends. Models can be developed using clustering techniques to find trends in data that are not visible in graphs and statistics.
These groups compare events and more or less express what factor is most important in these outcomes. More sophisticated data scientists can go even further with supervised algorithms and forecast future trends. They uncover factors that have influenced prior patterns by evaluating historical data and using them to make forecasts.
This might lead to creating new items and processes rather than just gaining knowledge. It is critical to understand the process so all parties can grasp what comes out in the end. Finally, to derive meaningful value from your project, your predictive model must be operationalized rather than left on the shelf.
Any business project’s purpose is to demonstrate its efficacy as quickly as possible to justify the job. The same may be said of data initiatives. This is the final step in completing the data analytics project, which is crucial to the data life cycle as a whole.
One of the most common blunders in machine learning is believing that once a model is constructed and deployed, it will continue to function normally indefinitely. On the other hand, models will decrease in quality over time if they are not constantly refined and fed new data.
Ironically, you must accept that your model will never be entirely “complete” to finish the data project effectively. The project needs constant analysis, retraining, and the building of new features to remain helpful and accurate.
Mindbowser has a commendable team of full-stack data scientists, engineers, and application developers who can speed data-driven solution invention and deployment. As a data science consulting firm, the organization combines substantial cross-industry expertise backed by scientific rigor and deep knowledge of state-of-the-art approaches to develop, build, and deploy tailor-made data solutions.
As a data science service provider, the team works with clients to identify use cases in their processes where data-backed insights might help. With Mindbowser holding the reins, you no longer need to go through a learning curve or hire expensive data scientists. The company provides specialized data science solutions to utilize and incorporate your confidential data into your process. Moreover, the company works under strict policies to handle all data with care.
When you include data science into your operational efficiency and effectiveness initiatives, you reduce the likelihood that another company will understand their customers better, provide services more effectively, or enter new markets than you had previously considered. Data science specialists at Mindbowser may assist you in ensuring that your company is ahead of the pack and that you are systematically exploring all options for success.
Mindbowser and team are professional, talented and very responsive. They got us through a challenging situation with our IOT product successfully. They will be our go to dev team going forward.
Founder, Cascada
Amazing team to work with. Very responsive and very skilled in both front and backend engineering. Looking forward to our next project together.
Co-Founder, Emerge
The team is great to work with. Very professional, on task, and efficient.
Founder, PeriopMD
I can not express enough how pleased we are with the whole team. From the first call and meeting, they took our vision and ran with it. Communication was easy and everyone was flexible to our schedule. I’m excited to...
Founder, Seeke
Mindbowser has truly been foundational in my journey from concept to design and onto that final launch phase.
CEO, KickSnap
We had very close go live timeline and MindBowser team got us live a month before.
CEO, BuyNow WorldWide
If you want a team of great developers, I recommend them for the next project.
Founder, Teach Reach
Mindbowser built both iOS and Android apps for Mindworks, that have stood the test of time. 5 years later they still function quite beautifully. Their team always met their objectives and I'm very happy with the end result. Thank you!
Founder, Mindworks
Our CISO was extremely impressed by Mindbowser’s work. It is pretty rare to see this kind of clean security report so early in the company’s journey. Huge Thank you for the disciplined approach here.
Founder, TrestleIQ
Mindbowser has delivered a much better quality product than our previous tech vendors. Our product is stable and passed Well Architected Framework Review from AWS.
CEO, PurpleAnt
The flexibility and capacity of the Mindbower staff has been impressive.
CEO, ProofPilot
I am happy to share that we got USD 10k in cloud credits courtesy of our friends at Mindbowser. Thank you Pravin and Ayush, this means a lot to us.
CTO, Shortlist
Mindbowser is one of the reasons that our app is successful. These guys have been a great team.
Founder & CEO, MangoMirror
Kudos for all your hard work and diligence on the Telehealth platform project. You made it possible.
CEO, ThriveHealth
Mindbowser helped us build an awesome iOS app to bring balance to people’s lives.
CEO, SMILINGMIND
They were a very responsive team! Extremely easy to communicate and work with!
Founder & CEO, TotTech
We’ve had very little-to-no hiccups at all—it’s been a really pleasurable experience.
Co-Founder, TEAM8s
Mindbowser was very helpful with explaining the development process and started quickly on the project.
Executive Director of Product Development, Innovation Lab
The greatest benefit we got from Mindbowser is the expertise. Their team has developed apps in all different industries with all types of social proofs.
Co-Founder, Vesica
Mindbowser is professional, efficient and thorough.
Consultant, XPRIZE
Very committed, they create beautiful apps and are very benevolent. They have brilliant Ideas.
Founder, S.T.A.R.S of Wellness
MindBowser was great; they listened to us a lot and helped us hone in on the actual idea of the app. They had put together fantastic wireframes for us.
Co-Founder, Flat Earth
Ayush was responsive and paired me with the best team member possible, to complete my complex vision and project. Could not be happier.
Founder, Child Life On Call
As a founder of a budding start-up, it has been a great experience working with Mindbower Inc under Ayush's leadership for our online digital platform design and development activity.
Founder, Courtyardly
The team from Mindbowser stayed on task, asked the right questions, and completed the required tasks in a timely fashion! Strong work team!
CEO, SDOH2Health LLC
Mindbowser was easy to work with and hit the ground running, immediately feeling like part of our team.
CEO, Stealth Startup
Mindbowser was an excellent partner in developing my fitness app. They were patient, attentive, & understood my business needs. The end product exceeded my expectations. Thrilled to share it globally.
Owner, Phalanx
Mindbowser's expertise in tech, process & mobile development made them our choice for our app. The team was dedicated to the process & delivered high-quality features on time. They also gave valuable industry advice. Highly recommend them for app development...
Co-Founder, Fox&Fork
