Conventionally, businesses have been complacent with simple relational database management system (RDBMS) and data warehousing architectures. However, these simple architectures have become inadequate amidst the ever increasing volume, variety and velocity of data. Though technical, this article examines and highlight how businesses big or small can leverage on big data to meet their current and future needs. Furthermore, the article also highlights best practice tools to help business harness and manage a wide variety of data from multiple sources such as social media and business systems.
In this data driven world, businesses are collecting large volumes of data through their day-to-day interactions with customers. These ever increasing volume of both structured and unstructured data requires new mechanisms and methods of handling data, thus ensure that businesses gain the much needed insight to improve their decision making and profitability.
We are seeing a huge interest in big data, visible in the creation of new start-ups specialising in big data analytics. Moreover, existing businesses are instructing their IT teams to carryout real time data integration, cleansing and blending across an ever growing variety of data sources. The goal of exercises such as this is to answer the question of how businesses can extract tangible value and useful insight from the silos of data that they have collected.
Business Intelligence or BI for short has emerged over the last decades as a set of techniques and tools for collecting and visualising raw data into insightful information that help business uncover flaws, strength, failures and successes in their critical operations. What seemed to be a stable arena of BI has drastically transform over the years, enabling pioneers and early adopters to benefit from the self-service visualisations, machine learning and predictive analysis. Tools such as Hadoop and Kafka have become so important and useful in any data warehousing environment because they prove to be reliable and robust.
For example, Hadoop (an open source software framework developed with need to process big data in mind) has become the standard for big data analytics. Hadoop changes the way an enterprise stores, process and analyse its data. Moreover, the rise of big data has also necessitated the need for NoSQL databases, in-memory and alike. This is due to the unstructured nature of the data in big data. It’s not only about obtaining value from the data but businesses should also consider how they administer and manage their ever growing data. Thus, ensuring that sensitive data is protected, and non-sensitive data is open to the public.
Despite of the successes of tools such as Hadoop and Kafka, some businesses are still reluctant to have them as part of their data warehousing and business intelligence stack for mere reasons that they are open source tools. This is driven by fallacious believes that open source tools do not have adequate support, thus businesses will lose money when they encounter problems because it will take them long correct the faults as there’s no dedicated vendor. This claim could have been true 20 years ago, but with rapidly technological development open source has become the new enterprise, with a large dedicated community of users always willing to help.
Although even before the term big data was coined, businesses manually analysed the data that streams into their business using spreadsheets to uncover trends and acquire useful insights. The difference between this and big data is speed and efficiency. Whereas in the past businesses manually analysed the data they collect to make future decisions, today businesses can leverage on the processing speed that comes with big data to uncover insights for immediate decisions making.
Big data present enormous amounts opportunities for both small and large businesses, as it helps them harness and consolidate the data that streams into their businesses, use it to identify new opportunities in the market. This will in return help businesses make informed decisions, thus improve operations and profits. Data has become the most valuable asset of any business, thus it is important for any business big or small as long as they have a website or are presence on social media and even a women selling Kapana at her home can collect data about the customer experience with her kapana. Even she needs a strategy how to collect, use and protect this useful information.
In conclusion, if you think that big data isn’t an essential for your business, you are definitely missing out. With strong conviction, I believe that big data analytics is important for every business, from the biggest corporates to sole traders and informal businesses, as it provides new approaches that holistically change how we do business.
*Lameck Mbangula Amugongo is country Ambassador of 1 Billion Africa in Namibia. He holds B.IT: Software Engineering, B.Hons: Software Development (Cum Laude) and currently pursuing MSc. Computer Science