Too Big to Ignore | Phil Simon

Summary of: Too Big to Ignore: The Business Case for Big Data
By: Phil Simon

Introduction

Welcome to the world of ‘Big Data’ – an ever-growing and powerful entity, fueled by our rapidly evolving digital landscape. In ‘Too Big to Ignore: The Business Case for Big Data,’ Phil Simon guides you through the intricacies of enormous data sets, their genesis from our changing consumption patterns, and their tremendous potential for businesses. Along the journey, Simon also delves into the challenges that come with handling Big Data, including unstructured data, data evaluation, and addressing privacy concerns.

Understanding Big Data

Big Data refers to massive and complex data sets that cannot be easily processed. The surge of Big Data is attributed to the transformation in our consumption behaviors, triggered by the plummeting cost of technology, especially in storage and bandwidth. The accessibility of smartphones, cloud computing, and broadband connections has resulted in continuous data consumption and generation. Consequently, this has fostered constant data creation, which culminates in Big Data. This cheap technology allows people to contribute to Big Data in various ways. For instance, modern technology enables the uploading of 48 hours of video content to YouTube every minute, and over 200 billion videos are viewed each month. The availability and significance of Big Data are real, but how to utilize it is the question.

The Power of Unstructured Data

Big Data is not just about quantity but also involves unstructured data that cannot be put into tables. Unstructured data accounts for more than 80% of organizational data today, and if well-managed, it offers great opportunities for gaining insights into consumer behavior. Netflix, for example, tracks where, when, and how many times their movies are watched, which devices their users watch them on, and even monitor people’s comments about the company on Facebook and Twitter. In 2011, Netflix lost 800,000 users after rebranding their mail service and repricing DVDs, but they were able to make a comeback after evaluating social media discussions and eliminating Qwikster.

Analyzing Unstructured Data

Learn about time series and heat maps for extracting insights from unstructured data.

The process of evaluating unstructured data can be overwhelming, given its massive volume. However, two essential techniques can help to make sense of it. The first one is time series analysis, which studies the data over time, identifying long-term and seasonal trends, irregular fluctuations, and correlations between variables. It helps to extract valuable insights that aren’t evident at first glance, such as employees’ spending habits related to their payday dates or a local event that boosted sales.

The second technique is heat maps, which can represent large sets of variables using different colors. Heat maps are a more intuitive and informative way of presenting information than traditional reports or graphs that can only relate two variables. They help to summarize data and discover patterns that would otherwise be unnoticed. Imagine a bookstore’s heat map, which can show the types of books sold, the most popular genres, the location of sales, and the quantity of sales per genre. A lot of red or yellow in one area might indicate high sales in a given neighborhood, and blue or green might indicate low sales.

By using these two techniques, companies can make better decisions based on accurate and comprehensive analyses, without being misled by temporary fluctuations. Regardless of the data’s complexity, valuable insights can be extracted, leading to opportunities to become more efficient and effective.

Big Data Management

Big Data platforms require versatility for efficient processing. Hadoop is a complex tool that breaks down tasks and processes subtasks individually. Outsourcing Big Data calculations to tech companies such as Kaggle can be cost-effective. Kaggle allows posting of Big Data tasks for data scientists to solve and suggest usage. Finding the best way to manage Big Data is crucial for each company’s success.

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