Let’s talk a little bit about big data. This is such an important buzz word in technology and data management circles these days. I think, however, that sometimes the nuances get lost. Big data is great, and has amazing potential applications for improving business processes, marketing opportunities, and customer identification, among others. Big data facilitates AI and machine learning, giving us unprecedented insights into patterns of behavior and process improvement opportunities. But the flip side of this is that big data also gives us massive amounts of ‘stuff’ to store and sift. I don’t mean to say that this data isn’t valuable. But without a solid strategy for utilizing and extracting meaning from this data, it can become costly clutter.
Big Data has A Big History – Big data is a concept that has been around for a while. Data storage and processing machines were created throughout the 20th century to handle increases in record-keeping needs corresponding to cryptography and security efforts, as well as governmental programs like Social Security and tax management. The British developed Colossus in 1943 to filter through Nazi transmissions and identify patterns for code-breaking. This is essentially the first data processor of the modern era. Since that time, the capabilities and applications of data processors have grown significantly, giving rise to the current age of data overload.
The Modern Rise of Big Data – In recent years, thanks to the advent of social media and the reinvention of the internet, we are creating data at an unprecedented rate. This represented an opportunity for many startups to process this data and identify relevant patterns that could be useful for industry and government. This modern definition of big data is the exciting buzz word that everyone wants to hear about. Companies want to jump on this big data bandwagon, contracting out or establishing in-house data processing teams. But is this really useful, or are these companies drowning in data?
Make Use of Big Data with Analytics Tools – Big data generally refers to quantities of data that are too big for traditional methods of business intelligence to analyze. In other words, big data is so massive that you can’t possibly do anything with it unless you have the right tools and strategies. In order to create value out of big data, it is important to have the ability to translate that big data into usable insights. This means robust data analytics tools and in-house or contracted data scientists to manage them. Check out our blog article 3 Top Analytics Tools To Boost Your Productivity for more insight into some of the industry’s leading analytics tools.
Develop a Team to Manage Big Data – It’s not just about the tools, it’s also about the team. Data scientists are a valuable commodity right now, and the growth rate of big data means that these high-valued analysts may be hard to find and expensive to retain. For large enterprises with a robust infrastructure, a data science team may make sense. For smaller companies, this may not be in the budget. Contracted teams of experts can help fill the gap in the market, providing expertise for clients interested in utilizing big data with a smaller IT budget.
Whatever your goals are, its important to understand the benefits and challenges of big data before jumping head-first into the data lake. Identify real market opportunities and a demonstrable need before committing to a big data strategy. For many companies, the benefits are worth the cost, but for some they are finding themselves drowning in data and unable to manage the bulk.
Dobler Consulting LLC is a leading provider of database services, premier software development, and information technology support, servicing clients ranging from small businesses to FORTUNE companies across multiple industry verticals. For more information about how Dobler Consulting can help you design your data analysis strategy, visit DoblerConsulting.com or call us at +1 (813) 322-3240 (US) /+1 (416) 646-0651 (Canada).