In a highly dynamic world, businesses are investing in statistics both to keep up with the competition and to predict the future trends of business in order to remain relevant. In this complex analysis of both structured and unstructured data, they will need to use other tools as the traditional tools can only handle structured data. So, what features should big data tools really have?

Before we can discuss the features of big data tools, let’s demystify “big data” and its purpose in the world today.

What is “Big Data?”

First, big data is a set of both structured and unstructured data that can be analyzed to predict trends, discover new preferences and offer big data solutions. These data may include and are not limited to social media, browser behavior, music, videos, web search, customer transactions, online books, search logs, etc.

Additionally, as the Internet of Things (IoT) takes the world by storm, they add to the sets and quantity of data that could be analyzed by the available data tools on the market.

So, big data isn’t necessarily about the size of the data generated for analysis but rather the technologies put in place to manage, restructure and derive meaning from these sets of data. The characteristics of big data are:

  • Variety: These are the different sets and structures of data generated every second
  • Volume: Refers to the large amounts of data; both structured and unstructured generated.
  • Velocity: This is the speed at which the data enters the internet and cloud services for storage and processing.
  • Veracity: The data is generally in its purest forms. Unstructured, uncategorized and messy. This is perhaps the reason why it can no longer be analyzed by traditional means.

These sets of data can only be analyzed by the big data tools which are programmed to handle different data sets, process them and come up with meaningful statistics that could help a business move forward confidently into the future.

Rapidly expanding Big Data space

In the past, only large multinationals and corporations had the wherewithal to acquire big data tools within which they could analyze business trends, predict the future and edge out competition. The big data space has grown in leaps and bounds making these formerly expensive tools to become accessible to both small and midsize businesses.

According to Forbes, the big data revenues for software and services will be worth $31B this year after a 14% increase from last year. In fact, Wikibon puts the Compound Annual Growth Rate (CAGR) of big data to be 10.48%. The value of big data in 2027 is predicted to hit $103B.

This just shows how critical the big data market is, and more so the tools used to analyze raw data and organize them into logical metrics that could be used by business decision-makers to spur growth, change tack and weather competition.

What are the features of big data tools?

A great big data tool should have the following features so as to reduce the complexities around getting insightful business statistics.

  1. Should offer embeddable results: Your big data tools should allow the data to be used in other decision-making applications to provide integration and ease of presentation.
  2. Provide for data exploration: A great big data analytics tool should give users a free hand in determining which sets of data they are analyzing in order to investigate the desired metrics.
  3. Data wrangling: The big data tool should provide data analysts with the capacity to organize, interpret and classify messy raw data into more clear labels that can be understood by business decision-makers.
  4. Support varied analytics: A good big data tool should be able to flexibly support different types of big data like predictive analytics, machine learning and real-time analytics.
  5. Scalability: A good big data tool should offer users the freehand to analyze complex data for longer periods of time. It should be able to adapt to the growing needs of the business enterprise and the expanding market metrics to be analyzed.

To ensure you get Return on Investment (ROI) the choice of your big data analytics tool will play a critical role, whether it is determining your business metrics, evaluating your customer preferences or investment decisions. The above-discussed features should guide you in making the right choice for the success of your business.

 

 

 

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