Why data analytics is important for companies?

Why Data Analytics is so Important for Companies?

The world of data can seem like an infinite maze for some. Knowing when to start investing in the collection and inspection of data is a tricky thing to do, and depends on the industry the startup is in.

But even though some companies can survive without the use of these tools, nowadays, with technology growing so rapidly, it’s recommended to start focusing on it in the early days of your company.

Out of people who have a minimal understanding of the world of data, only a few people know the meaning of certain disciplines if they’re not working directly in the field. Data entry, web hosting, device fingerprinting, and analytics will probably play a big part in your company, therefore it’s important to know what they mean, and how you can utilize them.

Why Data is so Valuable?

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Firstly, data entry is a service focusing on coding information such as personal details, billing information, online forms, accounting information, and more. This data is later stored for further inspection, otherwise known as data analysis.

While the term may sound perplexing, it is can be referred to simple tasks when doing simple email collections for PR activities or email campaigns collected through newsletters sign-ups.

Data analytics can be performed by simple online entrepreneurs or rising startups that wish to understand their target and cater to their needs.

Today, most companies collaborate with a data entry business or hire a professional to gather the needed information for them. And while freelance entry data specialists are harder to find, they’re a better investment in the long run for your company, as they’re consistent, and cheaper at the end of the day.

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After collecting all the needed information, this data is inspected, cleaned, and transformed via the analysis process. This helps companies discover useful information, connections, and it can also assist in making decisions.

And lastly, data analytics is the overarching science that encompasses the complete management of data. It’s very similar to analysis, as it’s the process of examining data to draw conclusions about gathered information.

But because this discipline embraces the complete management of data processing in the company, most people who value high-quality “data handling” in their company opt for hiring data analytics experts, rather than a data entry specialist and a separate analysis expert.

In this article, all of the above-mentioned aspects of data analytics will be broken down, from finding the right team, all the way to utilizing your finds the best way possible. Using the right software, and hiring a few specialists can make you the competition to look out for in your industry in no time.

Supporting Different Departments

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Investing in the right team to handle your data processing is the most important thing when getting started. Data analytics is a complicated science, and you’ll need experts to guide the way through the process.

Old-timers will know that data analytics was once a thing Excel enthusiasts played around with. But over time, it has become a science that requires specialized skills and experts to understand and handle.

While some businesses still manage with the use of Excel and Google Sheets, growing companies will need a team of advanced specialists if they want to survive.

Your team should consist of people with above-average spreadsheet skills, data analytics abilities, programming skills, and a good understanding of statistics. When hiring your team, you should not lose sight of your company’s needs and goals.

Data Analytics

This is especially important because apart from the dangers of hiring someone who doesn’t understand the science, there’s also the danger of hiring someone who is overspecialized. A candidate with a Ph.D. and 15 years of experience may seem promising, but you probably don’t need that level of expertise, and perhaps they won’t even be able to perform smaller tasks that you have to offer.

The best advice for startups is to find individuals who are highly talented with room to grow. They will most likely be kinder on your finances and will adapt well to your business. Additionally, these younger talented people will more likely be grateful for the varied work and will grow to be loyal employees in the long run.

The “Right” Data



As mentioned before, data analytics is a complicated science that embraces most tasks in data processing. But it all starts with the quality of the data provided, and believe it or not, there is such a thing as good data and bad data.

Before getting started you need to make sure that you have data suitable for accurate and meaningful analytics. The best way to do this is to consult with your newly hired team. The reason why that’s better than consulting with an outsider before the hiring process is twofold.

Firstly, it costs a lot to consult with an expert in data analytics, and when you’re not sure what they’re talking about, it’s easy for them to mislead you, or for you to misunderstand each other in a vague, one-hour meeting.

The second reason, and the most important reason, is that these people will be in charge of the project. The people you hire will all have a preference when working with data, they will already know your needs and goals, and they’ll have a grasp on the company’s foundations.

This means that they’ll not only have your needs in sight when working, but they’ll know exactly what they need in order to get the job done correctly, and on time. On the other hand, if you listen to an outsider, your team will be forced to work with ingredients “pre-organized” for them.

The best example for this could be hiring a head chef in a restaurant, and organizing and filling the kitchen to your preferences before they get there.

After consulting with your team, you’ll have clear insight into what you need in order to get the best results. If you’re an e-commerce company, you’ll probably be using the data collection software of social media platforms, and Google Analytics. You may also need some extension packages depending on your needs.

On the other hand, a video game-producing company could use software that analyzes click patterns for example, as that’s something that can improve the product over time. 

The amount of software available on the market is in the millions, and most of them are useful. There’s no way you’ll be able to pick and choose which five you’ll be using, which is why it’s better to consult with your team before getting started.

Also, a lot of software does similar things, and it’s up to the preferences of you and your team which one you’ll choose.

When deciding which tools you should be using, you also need to decide what data to collect. This decision is based on thorough research on your part, and it’s information that’s best established before involving experts. This will determine which tools you will use, and what your goals are. 

This is also the definition of “good” data, because the more of the right data you collect, the more effective the analytics will be. Whereas if you invest in other forms of data and other tools, you’ll probably find yourself stuck in one place, as neither the product nor the company has improved over time.

Measuring Results

data analytics steps

After hiring your dream team, and setting a goal for yourself, you need a sure-fire way to measure if this process is working or not. For this, you need to understand what success looks like for your analytics team.

First, you gathered data, then you inspected the data, came to a conclusion, and utilized that conclusion in your actions. For example, you can use gathered data to fine-tune your advertising techniques.

You can also react to the deterioration of user satisfaction quicker and more efficiently due to data analytics.

This directly translates to the use of targeted content, which could not be possible without the use of data analytics. You’ll be able to clearly see the requirements and needs of your users, making all marketing campaigns more personal for each consumer.

Most social media platforms already have a mode of measuring a post’s relevancy over time, and this data can be used to oversee each post’s performance. Seeing these numbers improve, or even change for that matter, is a clear sign that your data analytics team is working as it should.

Decision Making

data analytics investment

A huge part of data analytics that you’ll see right away is the elevation of the decision-making process. Data can not only be used in advertising or monitoring user satisfaction but also internally.

You can use your results to make smart, calculated, and intelligent decisions about your startup. It also helps identify patterns, trends, keywords, hashtags, conflict areas, successes, opportunities, and competition. Therefore, this process can pinpoint the next steps you should take as a company.

Understandably, this is one of the main qualities that attract startups to data analytics, as this help can elevate your entire company in no time! It’s truly something that can make your company reach goals in a year you thought would take five.

Finding Quality Investors


Most startups or small enterprises need the help of an investor to get started. And nowadays, most high-end investors demand experienced analytics experts as an early hire, even before you have enough data to work with.

This is almost a guarantee for them, and a point of feedback they can count on. Considering this, it could be smart to start by hiring a data expert early on.

Also, as your company grows, it’s more likely that you’ll be looking for the help or collaboration of high-end investors along the way for projects and expansions.

Here, you’ll definitely need a data analytics team to convince investors to tag along by showing numbers, statistics, goals, and other very important information, making your case.

Today, our world is basically a giant web of data. And in order to build anything, you need to understand how they work, and how they can be sculpted to your liking. Data analytics helps in exploring patterns and connections in this web, using them to your advantage. Through the evolution of data, building a business is becoming similar to architecture or sculpting.

Final Remarks

Building intellectual properties are becoming more technical, logical, and strategic. The use of data science makes it more likely that your startup makes an impact on the world. In conclusion, a good data analytics team could be what helps you keep up with the changes in our everyday lives.

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