Data Analytics Tools: Features and Functions

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analytics tools

Today’s business environment is inherently data-driven. Businesses need data to stay competitive and grow their market presence – data is regarded as the “currency” of the modern world and the key to the future. Data analytics, in turn, is the process of discovering trends and patterns in large amounts of data to make intelligent decisions. It leads to better operational efficiency, increased sales, and improved product innovation. Data analytics tools provide everyone in your business with the capability of unlocking value from data-powered information.

Analytics Tools: The Game Changer

You cannot afford to operate in “silos” anymore, and you also cannot afford not to analyze the wealth of information that surrounds you. With the right data analytics tools, anyone can leverage the power of big data to improve operational efficiency and grow their business. This article serves as a brief guide on the best data analytics tools for any business.

As a related activity, Data Management is crucial to the success of business analytics. Once data is collected, it must be managed. Your company’s Data Management strategy should be based on the needs of your organization. For example, if you sell health and beauty products, you probably do not need the same level of Data Management in terms of regulatory requirements that a bank or technology company would need.

Business Analytics: The Role of Tools

To perform data analytics at the highest level possible, analysts and data professionals use tools and software for a wide variety of tasks, including data preparation, algorithm execution, making predictions, and automating routine analytics processes like visualizing and reporting the data. 

Although there are many data analytics solutions on the market, data analysts have the tough job of selecting an appropriate tool wisely. Below are some of the most important analytics functions available across brands, including key features of each based on various types of analytics processes. 

The Data Analytics Platform

A data analytics platform offers an ecosystem of technologies and services that are required to perform analysis on voluminous, complex, and dynamic data. An essential consideration in analytics is the data source from which data must be retrieved, combined, interacted with, explored, and visualized from many angles. 

A comprehensive data analytics platform incorporates several tools with various capabilities, from predictive analytics and data visualization to location intelligence, natural language, and content analytics. Its main scope is to turn every kind of data into actionable insights for real business outcomes.

There are many different kinds of data analytics tools, and choosing the right one for your business can be challenging. After all, you do not want to invest in a tool that is unlikely to help you achieve your business goals. The best way to choose the right data analytics tool is first to explore, analyze, and list your specific business needs, then look for tools available in the market that best meet those needs. 

The IDC estimates that over 175 zettabytes of data will be created globally by 2025. Thanks to citizen data analysis, that market points to a $49 billion opportunity. A Forbes author offers five key trends in analytics worth noting:

  • Automation of business processes
  • Democratization of analytics
  • Transformed user experience 
  • Automated (augmented) platforms vs. fragmented tools
  • Analytics as a core business function

According to industry surveys, the most popular functions of a one-stop data analytics platform are:

  • Ease of onboarding and use 
  • Support for disparate data sources
  • Collaboration
  • Scalability
  • Visualizations and dashboards
  • Unified data analytics engine
  • Automated data cleaning
  • Automated ETL
  • ML-powered Data Modeling
  • Statistical functions
  • Automated BI capabilities
  • Purpose programming languages
  • Predictive analytics functions
  • Data Science tools

Choosing the Right Tools

So, you have decided to invest in data analytics tools. You’re excited about the prospects of using data to make better decisions, identify trends, and uncover patterns that can help improve processes and boost output. But where do you start? Fortunately, there are many options available when it comes to choosing data analytics tools that will serve your needs.  

Different Types of Tools

The common solutions that analytics software vendors offer today fall into two broad categories:

  • Data ingestion or data engineering software to transform raw data into a machine-readable format and load it on the analytics platform for analysis
  • Data analysis software with core features and functions for all types of data analysis

Before you choose data analytics software, you need to ensure that it’s tailored to your needs. Additionally, you need to consider the following factors from the marketing standpoint: 

  • Scalability: This is one of the most important factors to consider when choosing data analytics software. It is essential to identify a vendor with a scalable data platform and a proven track record. 
  • Cost-effectiveness: This factor is just as important as the previous one. It’s essential to identify a vendor that provides you with the best value for money.
  • Capabilities: It’s essential to identify a vendor with an extensive data platform and robust set of tools and features. This ensures that you are able to leverage all your data resources.
  • Customer support: It is also essential to identify a vendor with a customer support team that’s available during normal business hours.

This list of data analytics tools offers a useful comparative review of most tools, which may come in handy if you are exploring the market for a business solution. Additionally, a post cites Python and R as the best programming tools; Excel as the perfect data collection and analysis tool; Tableau, QlikView, and Power BI as the ultimate solutions for visual BI; SAS system as the go-to platform for all statistical analyses; and KNIME and Apache SPARK as the best open-source platforms for data analytics and reporting. The link offers further explorations of the individual features of each of these products. 

The Rise of Big Data Analytics

There has been an explosive rise in big data analytics. The main challenge of this type of data analytics has been filtering information from structured and unstructured data scattered across the diverse architecture. 

Emerging technical platforms offer enhanced power to understand and analyze big data. For unlimited access to big data, enterprises need to adopt big data software that integrates and analyzes larger sets of data on a massive scale. In addition, the software needs to enable improved visualization as well as statistical modeling. There are plenty of technologies and software vendors that can be branded as sources of big data analytics software. 

Big data, with its “high-volume, high-velocity, multi-variety data analytics,” needs software designed exclusively for that type of analytics. The special functionality required for big data analytics is described here. Here is another article that includes big data analytics tools capabilities.

An enterprise that applies data analytics tools will be better capable of understanding its business as well as its environment. It will enhance the power to convey the right decision at the right time and, as such, capture the right opportunities to develop a competitive advantage. 

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