The Future of Big Data

Big data refers to data sets that are too large and complex for traditional data processing and management applications. It has also become the catch-all term for gathering, analyzing, and using massive amounts of digital information to improve business operations. As data sets continue to grow, and applications continue to become more urgent, big data and big data operations are also becoming synonymous with cloud data technologies.

The evolution of the term “big data” has coincided with the rise of digital technology. As businesses gather and use an ever-increasing amount of information, IT professionals developed new methods for making sense of petabytes of data that overwhelmed traditional processes.

Those new methods rely increasingly on the cloud and cloud-native technologies. Big data has grown beyond what most organizations can house in on-premises server vaults, and it grows more every day. At the same time, the reliability and security of cloud-based platforms now meets or exceeds business needs.

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Why is Big Data So Important?

Consumers live in a digital world of instant expectation. From digital sales transactions to marketing feedback and refinement, everything in today’s cloud-based business world moves fast. All these rapid transactions produce and compile data at an equally speedy rate. Putting this information to good use in real-time often means the difference between capitalizing on information for a 360 view of the target audience, or losing customers to competitors who do.

The possibilities (and potential pitfalls) of managing and utilizing data operations are endless. Here are a few of the most important ways big data can transform an organization:

  • Business intelligence - Coined to describe the ingestion, analysis, and application of big data for the benefit of an organization, business intelligence is a critical weapon in the fight for the modern market. By charting and predicting activity and challenge points, business intelligence puts an organization’s big data to work on behalf of its product.
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  • Innovation - By analyzing a periscope-level view of the myriad interactions, patterns, and anomalies taking place within an industry and market, big data is used to drive new, creative products and tools to market.

    Imagine “Acme Widget Company” reviews its big data picture and discovers that in warmer weather, Widget B sells at a rate of nearly double Widget A in the Midwest, while sales remain equal on the West Coast and in the South. Acme could develop a marketing tool that pushes social media campaigns that target Midwestern markets with unique advertising highlighting the popularity and instant availability of Widget B. In this way, Acme can put its big data to work with new or customized products and ads that maximize profit potential.
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  • Lowered cost of ownership - If a penny saved is a penny earned, then big data brings the potential to earn lots of pennies. IT professionals measure operations not by the price tags on equipment, but on a variety of factors, including annual contracts, licensing, and personnel overhead.

    The insights unearthed from big data operations can quickly crystalize where resources are being underutilized and what areas need more attention. Together this information empowers managers to keep budgets flexible enough to operate in a modern environment.

Organizations and brands in almost every industry are using big data to break new ground. Shipping companies rely on it to calculate transit times and set rates. Big data is the backbone of groundbreaking scientific and medical research, bringing the ability to analyze and study at a rate never before available. And it impacts how we live each day.

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The Rise and Future of Big Data

Early this century the rise of the relational database, public web access, wireless, and other technologies made the study and management of massive data lakes a real and present challenge that needed a name. In July of 2013 the Oxford English Dictionary adopted the phrase, “big data,” but it’s been around since as early as World War II to apply to working with massive amounts of information.

With the explosion of cloud technologies the need to wrangle an ever-growing sea of data became a ground-floor consideration for designing digital architecture. In a world where transactions, inventory, and even IT infrastructure can exist in a purely virtual state, a good big data approach creates a holistic overview by ingesting data from many sources, including:

  • Virtual network logs
  • Security events and patterns
  • Global network traffic patterns
  • Anomaly detection and resolution
  • Compliance information
  • Customer behavior and preference tracking
  • Inventory levels and shipment tracking
  • Other specific data that impacts your organization

Even the most conservative analysis of big data trends points toward a continual reduction in on-site, physical infrastructure and an increasing reliance on virtual technologies. With this evolution will come a growing dependence upon tools and partners that can handle a world where machines are being replaced by bits and bytes that emulate them.

Big data isn’t just an important part of the future, it may be the future itself. The way that business, organizations, and the IT professionals who support them approach their missions will continue to be shaped by evolutions in how we store, move and understand data.

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The Five Vs of Big Data

Industry experts have identified five major considerations to address when structuring a big data environment. Each of these should be addressed individually and with respect to how it interacts with the other pieces.

  1. Volume - Develop a plan for the amount of data that will be in play, and how and where it will be housed.
  2. Variety - Identify all the different sources of data in play in an ecosystem and acquire the right tools for ingesting it.
  3. Velocity - Again, speed is critical in modern business. Research and deploy the right technologies to ensure the big data picture is being developed in as close to real-time as possible.
  4. Veracity - Garbage in, garbage out, so make sure the data is accurate and clean.
  5. Value - Not all gathered environmental information is of equal importance, so build a big data environment that surfaces actionable business intelligence in easy to understand ways.

Big Data Analytics

The process of managing the Five Vs has come to known as big data analytics. Transforming what starts as raw streams of disparate data into information you can use to understand customers, markets and trends requires a blend of high-tech know how and informed market savvy. Big data analytics is a field that will continue to evolve at the same speed as data itself, and the relationship between the two will shape future business.

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How to Use Big Data

Getting a handle on all of the above starts with the basics. In the case of big data those usually involve Hadoop and MapReduce, two offerings from the Apache Software Projects.

Hadoop is an open-source software solution designed for working with big data. The tools in Hadoop help distribute the processing load required to process massive data sets across a few—or a few hundred thousand—separate computing nodes. Instead of moving a petabyte of data to a tiny processing site, Hadoop does the reverse, vastly speeding the rate at which information sets can be processed.

MapReduce helps. As the name implies this tool performs two functions: compiling and organizing (mapping) data sets, then refining those into smaller, organized sets used to respond to tasks or queries.

These and other tools from Apache are among the most trusted ways of putting big data to good use in your organization.

Getting Started with Big Data

At Talend, serving your big data needs is what we do. Drawing from more than 12 years of globally trusted operations, Talend provides the data agility modern businesses need to succeed.

Check out Talend’s free downloads to get started on building a better, faster, more intelligent big data environment today!

| Last Updated: May 4th, 2018

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