How To Harness Big Data And Effectively Use It

It’s time to stop conceptually discussing big data and time to start effectively and practically implementing it.

August 1, 2023 | Big Data |

How To Harness Big Data And Effectively Use It

In a recent guide, we took a deep dive into the world of data science and big data analytics and shared some ways through which companies could pivot to becoming a data-driven company. But should you? Is big data analytics really worth it for a legacy business? And what if your competitors are not data-driven either?

In short, yes. With almost everyone adopting data science strategies in some form in 2020, big data analytics is no longer a “nice-to-have” – it’s necessary to stay competitive, especially for a legacy business. And if you’re competing with non-tech companies, you can leverage big data analytics to gain an early advantage over competitors.

But getting to a point where you can effectively use data to make strategic decisions isn’t straightforward. Fortunately, there are hundreds of companies that have already harnessed big data analytics and there’s a lot that can be learned from them. So in this article, we’ll take a look at some of the use cases and how companies can effectively tame big data.

1. Product Development and Optimization

Companies like Amazon and Netflix completely rely on big data analytics to develop and optimize their products. By monitoring and analyzing customer behavior, needs, and wants they know where and what changes to make to their platform. For instance, recommendations are a crucial part of both their products and by monitoring how users react to AI-generated recommendations, they can make big improvements.

However, the use of big data to innovate and optimize products extends far beyond what Amazon and Netflix are doing. Companies can set up automated pipelines that capture, sort, and process large datasets and use it to make data-driven changes to their product.

2. Customer Acquisition and Retention

One of, in not the biggest, use cases of big data analytics is customer experience. By using big data to process years of data and metrics like time spent by users, conversions, and abandonment rates, companies can get a better picture of customer behavior. Data scientists can associate changes in customer acquisition and retention to new feature launches, marketing campaigns, design changes, etc. and use this information to reinforce actions that led to positive consumer behavior and eliminate those that led to negative behavior.

3. Improve Marketing Efforts

Monitoring and analyzing consumer trends and preferences is crucial for a successful marketing campaign. For a long time, most companies had to create their marketing strategies using the data published by large multi-billion corporations for two reasons. First, only the “big” companies could collect so much data, and second, only they had the required software and hardware to process it.

But things have changed a lot since then. Now companies can use CRM platforms to manage customer relationships and collect an incredible amount of data. And with cloud-based analytics, all of that data can be processed easily and affordably. The end result is that marketers now have access to data that affects their company directly and can use this information to build very personalized marketing campaigns.

4. Risk Assessment

Risk reporting, fraud, compliance, and real-time risk assessment are all things that companies today are using data science for. It’s an incredibly complex process that varies from organization to organization but in a nutshell, companies can train machine learning models to identify and flag risky decisions, compliance breaches, or fraud in day-to-day transactions. This is especially important for companies in industries like fintech where fraud is common and non-compliance very expensive.

Focusing on the Outcome is the Key

Big data analytics is an extremely powerful tool with virtually endless uses. However, the key to efficiently harnessing and using data is to focus on the outcome instead of just the process. If your company is only focusing on collecting and processing data without a predetermined objective, there is a risk of getting side-tracked and not being able to capture any impact.

Though big data can be highly automated and cloud-based, the data science required to get there is still talent-intensive, meaning business executives need to be selective about their use and have a very goal-driven approach to the entire process.

D3V Tech has worked with many companies in numerous industries to help harness the power of big data analytics and tackle the challenges that come with it. We use a cloud-based approach to lower costs and one-on-one brainstorming sessions along with comprehensive audits to identify areas of business that require the most attention and assistance.

If you have any questions about big data analytics and what it can do for your business, reach out to one of our certified cloud engineers today!

Author

Harsimran Singh Bedi

Steve Sangapu

Founder and CTO
Steve is an accomplished technical leader with over 20 years of experience and 7 patents from the USPTO. Most recently, he was a CTO of a DFW startup, LASH Delivery, that was acquired by a Fortune 500 company. In his free time, he enjoys coaching his daughter’s volleyball teams.

Related Posts

What Our
Clients Are
Saying

Working with D3V was hands down one of the best experiences we’ve had with a vendor. After partnering, we realized right away how they differ from other development teams. They are genuinely interested in our business to understand what unique tech needs we have and how they can help us improve.

Lee ZimbelmanWe had an idea and D3V nailed it. Other vendors that we had worked with did not understand what we were trying to do – which was not the case with D3V. They worked with us through weekly meetings to create what is now the fastest and most accurate steel estimating software in the world. Could not have asked for anything better – what a Team!

We used D3V to help us launch our app. They built the front end using React and then pushed to native versions of iOS and Android. Our backend was using AWS and Google Firebase for messaging. They were knowledgeable, experienced, and efficient. We will continue to use them in the future and have recommended their services to others looking for outside guidance.

Constrained with time and budget, we were in search of an experienced technology partner who could navigate through the migration work quickly and effectively. With D3V, we found the right experts who exceeded our expectations and got the job done in no time.

Protecting our customers data & providing seamless service to our customers was our top priority, which came at a cost. We are very satisfied with the cost savings & operational efficiency that D3V has achieved by optimizing our current setup. We’re excited about future opportunities for improvements through deriving insights from our 400 million biomechanics data points.

Our experience with D3V was fantastic. Their team was a pleasure to work with, very knowledgeable, and explained everything to us very clearly and concisely. We are very happy with the outcome of this project!

Jared Formanr

Jared Forman

CEO & Co-Founder, OSMix Music

Lee Zimbelmanr

Lee Zimbelman

IT Director, BLI Rentals

Terry Thornbergr

Terry Thornberg

CEO, Fabsystems Inc.

David Brottonr

David Brotton

CEO & Founder, Squirrelit

Dr. A. Ason Okoruwar

Dr. A. Ason Okoruwa

President, Bedrock Real Property Services

Ryan Moodier

Ryan Moodie

Founder, DARI Motion

Schedule a call

Book a free technical consultation
with a certified expert.

Schedule Call

Get an estimate

Fill out our form to hear back with a project’s cost estimate. No meeting required.

Get Estimate

Get in touch

Send a message to D3V team.

Let’s Talk