Every day at Perficient, we help clients develop new ways of interacting with customers, build contextual understanding in their decision making, and create new ways of business operations as a Smarter Process Practice.
In this article, I am going to describe a couple of data-related challenges businesses are facing as they embark on their digital transformation journeys and provide a cost-effective technology recommendation to address these challenges.
One challenge within Digital Transformation is non-traditional data, referred to as unstructured data. Some estimates predict that that 80 to 90 percent of all data in any organization is unstructured. The following are a few of the causes of the generation of unstructured data.
Application Development Revolution
The first is a result of a revolution in application development. Application developers are building large amounts of connected applications which are running on numerous devices such as cellphones, tablets, RFIDs, sensors, thermostats, and security cameras. This revolution in application development has resulted in an explosion in the amounts of data being collected. For example, it is expected that the number of smartphone users worldwide will surpass 2 billion in 2016. Customers expect an integrated experience across all of their devices, whether in physical stores, shopping online, and when talking with customer service on the phone. The business problem has become how to identify technology solutions that meet the business demands to build a unified customer experience and extract useful information in order to engage customers or build better products.
The second cause of unstructured data is social media. There is a growing need to perform analytics based on data from social media in order to build closer relationships with customers, or target specific market segments. Data from websites such as Facebook, Twitter, Google, and other third party vendors is being made commercially available to large corporations and small businesses alike. Now that organizations have access to this data, they need to determine how to best utilize social media data for marketing, to enhance customer experience, drive traffic to their websites, or obtain optimal positioning within search engine result pages. This is one of the reasons Chief Marketing Officers are becoming key decision makers in technology services selection. Organizations are gaining value from social media data by integrating it into their business as a part of their Digital Transformation.
Another cause is mobile data. According to Morgan Stanley, 91 percent of adults keep their smartphones within arm’s reach. People are generating large amounts of data such as text messages and location information. WhatsApp, a cross-platform mobile messaging app, or Zipcar, a vehicle sharing service that allows customers to reserve and unlock a car via mobile phones, are examples of businesses that have taken advantage of the use mobile data to create a new business that could not have existed 10 years ago.
Unstructured Data Management and Big Data
Unstructured data generated from the application development revolution, social media, and mobile devices is information which contains text and multimedia content that is nonconforming to pre-defined data models. Some examples include images, audio or videos files, heavy text documents, emails, locations, and webpages. Last year it was reported that Facebook alone stores 600 terabytes of data per day (adweek). Because unstructured data is rapidly growing, organizations are looking for technology solutions to process, store, and analyze it. Unfortunately, this data cannot be stored in traditional relational databases. The organizational challenge is how maximize the value of unstructured data to achieve a competitive advantage or risk becoming irrelevant.
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Unstructured data poses the biggest opportunity for organizations embarking on Digital Transformation challenges. The volume and complexity of unstructured data means that traditional methods of discovering, governing, and collecting information are no longer feasible. Therefore, organizations are evaluating Big Data technology because they are the most suitable technologies to address these requirements. Organizations that unlock insights from the harvesting, storing, and/or processing this unstructured data are able maximize it’s value.
What is Big Data?
IBM’s definition of Big Data is based on four categories: velocity, volume, variety, and veracity.
- Volume- is the scale in the amounts of data being created
- Variety – is the different forms of data being created
- Velocity – is the analysis of streaming data (the speed the data is generated and the speed analytics is required on the data)
- Veracity – is the uncertainty of the data (accuracy or validity of data being generated)
IBM Bluemix Big Data Solution
Now that we have covered the reasons for the change in the technology landscape, and the defined Big Data, lets review a quick and cost effective technology solution: IBM Bluemix.
Bluemix is IBM’s cloud based Platform as a Service (PaaS), where developers can quickly develop and deploy applications in an open cloud platform. It provides a method for an organization to prove out technologies, deploy, and host applications over the internet. IBM Bluemix offers over 200 available services that developers can integrate with their applications. These applications are grouped in the following categories: Boilerplates, Runtimes, Watson, Mobile, DevOps, Web and Application, Integration, Data Management, Big Data, Security, Business Analytics, and Internet of Things. IBM is also offering two architecture platforms on Bluemix:
Bluemix public is the core environment for developers to build applications using services that provide ready-to-use functions.
Bluemix Dedicated is an exclusive environment that is secured on a private network, but connected to the public Bluemix for service integration.
Cloud Makes it Possible
Bluemix makes it possible for applications to be quickly developed using pre-built assets exposed as APIs. Developers need not worry about managing infrastructure to host applications such as provisioning hardware, operatings systems, administering servers, and middleware. This typically takes weeks to setup in the traditional application infrastructure environment.
Bluemix is simple. Developers can also continue to use tools they are familiar with, such as eclipse. They can focus on writing code, in whichever tool or language they choose, and integrate existing services through API’s into their applications without having to learn a new programming language. The maintenance and upgrading of the infrastructure is also handled by IBM.
Bluemix is cost effective. This Platform as a Service based on cloud foundry IBM offers a pay-as-you-go option which is based on memory, IP address, and storage utilization. This means you pay a minimal monthly fee and are only billed for the resources you use.
The IBM Bluemix Big Data category provides the following services for big data management and refinement:
- BigInsights for Hadoop (IBM)
- dashDB (IBM)
- Geospatial Analytics (IBM)
- IBM Analytics for Hadoop (IBM)
- Insights for Twitter (IBM)
- Time Series Database (IBM) 2.9
These Big Data solutions include among others, Ambari, YARN, Spark, Knox, HBase, Hive, and an encrypted Hadoop Distributed File System (HDFS). You can sign up for a 30 day trial of IBM Bluemix here.
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