The proliferation of Big Data, Advanced Analytics, Machine Learning, and other such modern technologies is generating buzz. Every day, we hear how these technologies are helping companies better understand customer behavior and purchase habits, reducing costs, helping to generate better health outcomes, and increasing profits. So, what has driven this buzz? At a high level, it is driven by the convergence of the factors below:- Connected society – Today’s citizens are always connected, generating/exchanging data
- Internet of Things (IoT) – Sensors and bandwidth improvements have produced machines capable of communicating with one another and sending data through the internet
- Growth of social media – Twitter, Facebook, Snapchat, Instagram, Pinterest, Blogs, etc. not only produce vast amounts of data, but also present new opportunities to analyze and understand consumer sentiment
- Rise in consumer expectations – Consumers now demand personalized service, advertising, and attention customized to their preferences to influence action
- Commoditization of technology, emergence of new tools – Cloud computing and open source technologies allow for smoother data ingestion, storage, reporting, and advanced analytics
Large companies with ample resources have been able to take advantage and derive real value from this growing flood of data. Conversely, Small and Mid-Sized Businesses (SMBs) have been slow to adopt these new technologies. When speaking with companies seeking to harness these technologies for their enterprises, the misconception is that in order to gain real value, SMBs need to spend vast amounts of money and time. This is not true. SMBs are able to incorporate advanced analytics techniques that can extract insights from massive, dynamic and diverse data.
With that said, SMBs often face the following challenges as they begin their journey to modernize their data architectures:
1. Not having a well-defined strategy and roadmap, with clear measures of success
2. Managing business expectations that are fueled by daily success stories
3. Not defining how new technologies can fit into the existing architecture
4. Lack of technical skills, and knowing how to strategically develop these skills
5. Defining an appropriate process – one that allows innovation yet maintains quality
6. Making sure that the data used to make business decisions is governed appropriately
7. Selecting the right set of tools from a wide range of choices
8. Selecting the right partners to help along the way
