Data analytics, also known as data insights, is a booming industry and a sector of IT that is increasing. In the world of cloud computing, data is king, and with it comes endless possibilities to harness the information to drive business decisions and plan future strategies.
To be a leader in big data, it is essential to collect, process, and transform data collection. Businesses use AI routines to create intelligent workflows, and data scientists crunch results using complex modeling programs.
None of this would be possible without cloud computing. So join us as we discover the most innovative ways to harness data in the cloud.
Data analytics applies to almost any industry, but marketing and retail are two industries that thrive on accurate data. Companies need to use customer data to ensure they offer the right product or service to the right customer at the right time and place. Collecting data is relatively straightforward; however, creating accurate information based on the collected data is a huge challenge that takes teams of skilled data scientists and well-trained learning models.
As consumers, we create data for our favorite brands in shops and online. Our behaviors shift in response to local and national events. Take COVID-19; customer buying habits fundamentally changed during the pandemic, driving customers online. The consumer has weathered the pandemic but is now facing the challenges of a cost of living crisis.
Today, businesses must make critical decisions quickly, and data can give insights into customer attitudes and behavior. This knowledge gives your business the upper hand when retaining and attracting new customers.
You may be wondering how it is possible to get access to big data. There are several avenues to explore here.
- Purchase Data Sets: Did you know that you can simply buy this data from a global scale data business? There are several data collection agencies across the globe, such as CACI International Inc. Datasets that are available to purchase that include any credible information, such as customer habits and behaviors, geodemographic segmentation tools, financial services, and digital, lifestyle, and attitudinal characteristics.
- Create Your Own Data Sets: Nearly all businesses have at least one database containing information about their customers, sales, etc. Those that invest significantly in data analytics will gather all sorts of data, perhaps from their website using clickstream data or from surveys, sales orders, refunds, and returns. This is where we are seeing significant growth with data in the cloud as businesses offload these CPU-intense workloads to the cloud providers.
What kind of insights can you get from trained datasets? The possibilities are endless, but here are some of the standard data insights businesses may look for:
- Buying Habits: Learning how and why your customer buys is a critical business need. It enables you to create effective advertising campaigns and tailor customized marketing strategies. In addition, an accurate dataset will allow you to discover where your customers shop, what they buy, and why they buy certain products and services.
- Customer Engagement: Trained datasets can discover how customers engage with your brand in a physical and digital environment by learning customer interactions and preferences and predicting future behaviors.
- Demographics Insights: This type of data is critical to understand the people you serve; shared insights include gender, location, profession, and age. This data allows you to target high-value customers and learn who interacts with your business.
- Customer Acquisition Costs: This is the process of understanding the costs of getting customers to buy your products. Consider the marketing costs, advertising spends, salaries, running fees, and commissions.
- Marketing Insights: Businesses rely on marketing to get the word about products and services. Advertising can be costly, so understanding the campaign’s outreach is critical. Learn how much new business the campaign has generated, what demographics interacted with the campaign, and what campaign platforms were a success.
- Monte Carlo Simulation: Countless factors impact a customer journey. This simulator calculates the possibilities and options that may affect the customer’s purchase and determines the probability of an event happening. It can help predict failure.
- Factor Analysis: This data reduction technique takes enormous datasets and shrinks them to a small, more accurate dataset with actionable insights, making data lineage much more straightforward to visualize data trends and habits.
We have just scratched the surface of data insights; quite literally, the possibilities are endless. Other common examples include using data to predict fraud, credit defaulting risk, and customer profiling. In addition, the number of simulations available is growing daily; other joint analysis tools are regression analysis, cohort analysis, cluster, time series, and sentiment analysis.
Cloud computing opens the door to data analytics and insights. Cloud storage offers limitless space for your databases, datasets, and trained data, and cloud computing is available on demand to crunch numbers and process data cubes. Although performing this type of data modeling is challenging on-premises because you are always going to be restricted by the size of the infrastructure, you can leverage as much or as little as you need in the cloud.
Data organizations have the added headache of regulatory compliance, with regulations such as HIPAA and HITRUST to consider. Cloud-service providers work closely with their customers to ensure that they comply with the necessary compliance and regulatory guidelines. As a result, they are setting a precedent for data companies.
Atlantic.Net has been providing cloud hosting and managed services for over 28 years. Our cloud platform is available with service plans that can scale to any demanding workload. In addition, you can provision multiple configurations up to 32 vCPU and 192GB of memory, all backed onto ultra-fast SSD storage – perfect for crunching large data sets.
You can start your data journey right now by emailing [email protected] If you have any questions, please get in touch! Contact an advisor at 888-618-DATA (3282)