Wrangle Big Data Instead of Wading Through Data Lakes

Most of the data that has ever been produced has been generated in the past couple years, and most recently that data has come from mobile devices.

Whether it’s officially acknowledged not, this massive amount of data is affecting your company: Your company’s capacity to gain insights from Big Data and navigate real-time feedback will play a major role in its future success.

Handling and assessing data are now essential business practices. However, these tasks are not straightforward. Big Data requires a big strategy in order to be properly leveraged.

What are your goals?

Your goals for Big Data have the biggest influence on the design of your overall data strategy. Your company has to decide if it wants to raise efficiency, boost revenues, offer a better customer experience or improve its marketing strategy.

Your objectives ought to be “SMART” – specific, measurable, attainable, relevant and time-based. Any approach with just the sole objective of exploration is probably just going to cause confusion.

Embrace a proven strategy

Although the concept of Big Data is still relatively new to business, that doesn’t mean there aren’t proven Big Data strategies to choose from.

A Performance Management strategy consists of using transactional data like purchases and inventory levels to make more-informed operational decisions. This transactional information ought to be readily available inside any organization and leveraging it can offer insights into a variety of subjects associated with both short-term decisions and long-term planning. A Performance Management strategy is extremely useful for businesses with large historical databases, which can be easily be analyzed without much investment.

A Data Exploration strategy makes serious usage of data mining and study to discover solutions and connections that are not readily discoverable with basic information. This strategy can make it possible to locate new areas of information and draw out observations relating to customer’s behavior and priorities.

A Social Analytics strategy assesses non-transactional information on social media and user review sites. The strategy is focused on three main metrics: awareness, engagement and word-of-mouth. The results of this approach are greater insights on brand identity and public opinion regarding various products and services. A social strategy is also effective in anticipating spikes or drop-offs in demand.

A Decision Science strategy is more about looking at new possibilities rather than gauging recognized objectives. Rather than focusing on engagement analytics, decision science involves testing theories and ideation methods. This calls for comprehensive usage of text analysis to determine customer thought processes.

Develop a Big Data team

Without a suitable staff, conversations on Big Data may center around concepts and terminology that are not easily understood by decision-makers. A Big Data team should include statisticians to interpret findings and business analysts to package insights for decision makers, who are able to launch initiatives or make suitable changes.

Are you looking for top tech talent?

At SMCI, we help companies find the talent they need to embrace Big Data and other initiatives. If your company is currently looking for top tech talent, please contact us today.