Introduction

Data does not have any value until it becomes useful information that allows business owners to make logical decisions. Today, analytics can choose from a long list of data analytic tools. On the surface, it sounds appealing but a multitude of choices often overwhelms business leaders to make the right call.

Gartner defines big data as the high velocity, volume, and variety of data assets that need unique processing. This improves data discovery, process optimization, and overall decision-making. It is hard to talk about the perks and pitfalls of data analytics tools without bringing big data into the fold.

Data analytic solutions continue to make it easier for businesses to extract and review insights in real-time. On a global scale, business analytics and the big data market amount to over 175 billion. In fact, the current estimate suggests that this value will jump to $274 billion by the end of 2022.

From finance to marketing to product development to sales, using data analytic tools has become integral for business leaders to stay ahead of their business operations. Here are some of the essential benefits and limitations of using modern-day data analytic tools:

Benefits of Modern Data Analytic Tools

•  Monitor Behavioral Changes Among Customers

One of the best aspects of using an analytics tool is to keep a close eye on the behavior and preferences of your customers. Since behaviors, preferences, and tastes of customers change all the time, it makes all the more reason to utilize a robust data analytics tool.

Through a data analytics solution, an organization can better understand the expectations and desires of its customers. Customer data has become the Holy Grail because it allows organizations to understand the perception of their target audience.

•  Improve Work Efficiency

By using a data analytic tool, organizations can take their work efficiency to next level. And that’s because modern-day and advanced analytic tools are capable to analyze large data in an instant. Analysts can display, formulate, and review the same data to achieve short-term and long-term organizational goals.

What’s more, is that the use of modern analytic solutions creates an efficient workplace environment. Through data analytic tools, managers can share useful insights with the employees and address inconsistencies. The faster managers address these gaps, the more productive the workplace environment becomes over time.

•  Heightened Product or Service Quality

Most analysts use data analytics tools to improve the overall quality of a product or service.  Of course, this change is gradual and takes some time to positively impact the quality of products or services. For instance, analysts use data analytics tools to spot and address issues and create more value in each product or service.

As a result, the user experience is enhanced and fosters more intuitive interactions. In fact, self-learning solutions now utilize data to better understand “how” customers interact with the tool. With automated data analytics tools, organizations can consistently improve the data quality, which in turn, will improve the quality of their products and services.

•  Targeted Personalization

It’s not enough to roll out attractive products or services – organizations now have to launch personalized products and services that cater to a specific target audience. Without a data analytic solution, it would be an extremely time-consuming effort to tap into the specific expectations and preferences of the customers.

But personalized touch on products through data analytic solutions has become standard practice. For instance, brands now commonly use targeted and personalized services based on individual customer requirements.

•  Improved Decisions Making

Data analytics has made it possible for business leaders to make logical and calculated decisions. Gone are the days when business leaders had no choice but to make instinctive choices rather than base decisions on insights and facts.

One of the main perks of using a data analytic tool is that it gives complete access and control to quality data that allows business leaders to transform operations. Better decision-making means more competitive advantage and more profitability.

Limitations of Modern Data Analytic Tools

•  Data Privacy Issues

One of the main concerns with data analytics tools is a potential compromise of data privacy. Today, breaches of customer data in the form of subscriptions, online transactions, and purchases are common. And some companies still collect valuable information from customers using data analytics tools without consent. The solution lies in more awareness and cautiousness from organizations to collect customer data and ensure data confidentiality and security.

•  Compatibility Issues

Data analytics often struggle to align a specific tool across teams and departments. More compatibility issues mean more restrictions on executives and business leaders to roll out effective changes. Without proper alignment and compatibility, communication falls apart between executives, teams, and departments of an organization.

•  Requires Continuous Commitment

Although analytics tools are not that difficult to use, they demand patience and continuous commitment from analysts and business leaders. After all, there are so much accurate data analytics models that can achieve. Not to mention, the ROI is never immediate. So, if an organization does not have access to its existing data, it is bound to take a lot of time to collect, process, categorize, and review the data.

Final Thoughts

The fact of the matter is that different data analytics tools come with different features. But the basic features and use cases of most data analytic tools are more or less the same. The features, usability, and setup are often what differentiates one platform tool from another.  The focus of analysts is usually to opt for the top-tier data analytics solution in the market to collect, analyze, and report data with complete confidence, convenience, and preciseness.  However, there are a lot of up-and-coming solution providers or industry-specific platforms that have unique tools and features s not often found on some of the top-tier solutions.  

The demand and utilization of data analytic tools are bound to open new windows of opportunities for organizations. With data analytics, organizations can achieve much better results. Business leaders can use data analytic tools to analyze historical performance as well as optimize businesses processes for years to come.

REFERENCES:

2. https://www.jigsawacademy.com/8-big-data-tools-need-know/
3. https://www.logianalytics.com/development-tips/7-pros-and-cons-of-using-open-source-data-analytics-components/
4. https://4datasolutions.com/pros-and-cons-of-data-analytics-platforms/
5. https://news.mit.edu/1995/mitranking

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