The concept of Big Data has dominated the enterprise technology scene for the past several years. It is a powerful tool that can transform companies… if used properly.
Seamless data integration solutions are vital to ensuring a successful Big Data initiative. In the video below, Brad gives an introduction to the guide.
This guide explains what Big Data is, the benefits of harnessing it, how robust data integration solutions enable the optimal use of Big Data, and how organizations use Big Data.
What Is Big Data?
There is probably no term more misunderstood in technology today than Big Data. While there is actually a universally accepted definition of it, Big Data still generates quite a bit of confusion.
Here is the actual definition. Big Data describes a voluminous amount of data. That information could be structured, unstructured, or semi-structured, and it has the potential to be mined for valuable insights that could help the company not only survive but flourish.
While there’s an accepted definition, Big Data still generates quite a bit of confusion.
Big Data has three characteristics, known as the “3 Vs”: volume, variety, and velocity. Volume refers to the large amounts of data (it could be in the millions, if not billions, of bytes), and there are many varieties of information available. Big Data also requires processors which work at a high velocity.
When you talk about Big Data, one part of the conversation invariably has to do with the origins of the information. Big Data can refer to information gathered from any source, and nowadays, there is no limit to the number of places from which you can gather data; there are real-time sensors attached to manufacturing equipment, click-through rates of marketing campaigns, and the number of likes a single social media post generates.
Big Data has three characteristics: volume, variety, and velocity.
In addition to the origins of the data, variety (as it relates to Big Data) also refers to types of information. There are structured data, which have been organized into a formatted repository and are easy to process and analyze. Unstructured data, conversely, is information that is not organized into a formatted repository, and as a result, is not easily processed or analyzed; examples include Word documents, PowerPoint presentations, JPEG images, and MP3 audio files. Semi-structured data is, as the name implies, not completely structured but not completely unstructured, either; rather, it has elements associated with it such as metadata that make machine processing and analysis possible.
The final “V,” velocity, is critical to understanding Big Data. Mounds and mounds of information are utterly useless unless you can process them. Human analysis of such enormous amounts of data is inefficient; you need a processor that can analyze the data quickly and effectively to provide answers to queries. That kind of processing requires a great deal of computing power; it could easily overwhelm a single server or even a cluster.
Two ‘Vs’ have been added to the original definition: veracity and variability.
Since the development of the original definition, two other “Vs” have been added: veracity and variability. Veracity comes from the Latin word for “truth.” Essentially, it refers to the accuracy of the data. If the information in your digital repositories is not accurate, it is not useful. Variability denotes the inconsistency in volume as well as accuracy, which are two issues CIOs must take into account.
What Are the Benefits of Using Big Data?
Despite the confusion surrounding Big Data, there are some clear benefits derived from utilizing this technology.
Researchers believe that using Big Data provides a competitive advantage over other firms in your industry. With access to volumes of information about many aspects of your business, you can learn more about what your customers want or how you could become more efficient.
For example, a vacuum manufacturer might discover that its customers are all complaining about the exact same feature of its latest model on Facebook. Tweaks to the design make the vacuum easier to use and boost customer satisfaction (which in turn increases profits).
Big Data provides a competitive advantage over other firms in your industry.
Gaining a competitive advantage is not the only benefit you can derive from using Big Data. The information you already possess can help you generate more profit by developing new products or services. Go back to the example of the vacuum cleaner manufacturer. After reviewing other online comments, the firm learns that many of its customers really want a two-year warranty (which it currently does not offer). Thanks to Big Data, the manufacturer can now offer a service that will satisfy its customers and earn it more money.
Another reason to use Big Data is that it can make processes more efficient. A study carried out by the Ivey Business School at Western University showed that up to a quarter of the effort that workgroups of knowledge workers expend is used in searching for data and then transferring it to another location, which is quite inefficient.
Big Data can make processes more efficient.
An additional positive aspect of utilizing Big Data is the ability to segment customers even further. Suppose that your current market segment is men who are 18-34 years of age. That is a broad audience; analyzing your data shows you that your most loyal customers are single men who live in mid-size and major cities and who are between the ages of 25-31. With that information, you can target those customers more easily and increase your revenues.
How Can Data Integration Solutions Help You Maximize Big Data Value?
Business leaders might not always realize that there is a treasure trove of data just waiting to be uncovered within their own company. However, that information tends to be locked away in silos, which can be difficult to tear down.
The rise of the data silo has a great deal to do with the proliferation of ERP software solutions. ERP software was supposed to replace separate departmental applications. At many companies, that vision was not realized, because the companies would implement multiple ERP suites (one for each branch or location).
There was no single version of the truth; within the same company, there were several competing sources of information.
As a result, there was no single version of truth. Within the same company, there were several competing sources of information, which led to poor decision making and missed opportunities.
Fortunately, this no longer has to be the case. There are a number of data integration solutions that enable organizations to break down digital information silos and allow them to maximize the value of Big Data.
Data integration solutions enable organizations to break down silos and maximize the value of Big Data.
How do data integration solutions work? They rely upon a process that retrieves heterogeneous information from a variety of sources (they could be internal or external, but many firms have so much internal data that they focus on that type of source first) and structures it so that it is easy to access and analyze. All of the information is now in one place; there is no more wasted time hunting down vital data.
There are a number of data integration solutions on the market. Choosing the right one for your company will depend on which data sources you have, what you are going to be doing with the information once you have integrated it into a single source, how large your firm is, and what resources and skill sets your workforce possesses.
There is no more wasted time hunting down vital data.
Although the aforementioned factors are crucial when it comes to selecting a data integration solution, there is one characteristic that it should have regardless of your company’s size, resources, or data sources. The data integration solution should be robust. It should be able to perform well no matter what the circumstances are and it should possess a wide range of capabilities.
Big Data Success Stories
There are a number of Big Data success stories; they come from real companies that have implemented data integration solutions to derive value from the information they already have.
In 2015, the Australian telecommunications firm Telstra announced it would be deploying a predictive analytics system that would identify network problems before they even take place. If it is not possible to prevent a problem from affecting service, the system suggests potential responses.
Telstra deployed a predictive analytics system to identify network problems before they even take place.
Lockheed Martin uses dark data (corporate information that has been sitting untouched for ages) to improve its project management. The company analyzes metrics from its programs to identify performance indicators. It also evaluates communications between employees about projects, which enables Lockheed Martin to predict which programs are performing poorly based on how personnel talk about them.
Big Data has changed the way Pemex, Mexico’s state oil company, handles maintenance at its refineries. The firm installed sensors on its equipment that would detect sound vibration. Abnormal sounds indicate equipment failure, and now that sensors notify them when something is not working, engineers can fix problems faster and significantly reduce downtime.
Engineers can fix problems faster and significantly reduce downtime.
Your business can also be a Big Data success story. Data integration through assimilation and consolidation is a vital chapter in that tale and we can help you make it happen. To learn more about integrating and mapping your data into a single source, contact us.
