Ask Bigger while reducing costs

By Benny Yehezkel

11.26.2022

What every CFO needs to know about how organizations can Ask Bigger while reducing costs

Every year seems to be bigger when it comes to big data. In 2022, around 2.5 quintillion bytes worth of data is said to be generated every day!

With the surge of cloud computing, machine learning, IoT, mobile data, and more, there is no doubt that the big data tsunami will only continue to grow every year.

And this continuous expansion of data is powering massive investments. To illustrate, the global big data and analytics market is estimated at $274 billion, representing a 62% increase over 2018.

This is no surprise, for as we all know the value of big data is tremendous, whether we mine it to extract insights about our market and customer dynamics or to understand the forces impacting operational efficiencies, or for predicting which channel will deliver the most leads from the upcoming marketing campaign, among many others.

But while the value of getting bigger answers from data can be very great, so can the cost to ask the bigger questions.

sqream cost

The cost of asking bigger

The cost drivers are many. They include the cost of building and maintaining a data warehouse with, hardware, electricity, real estate, and software.

There is also the cost of the professionals who build and maintain the data warehouse, as well as those who do all the data science required. For top tier global enterprises this can translate into dozens of millions of dollars.

Beyond build and maintenance, managing data and running the analytics can also be cost intensive. And moving this data from on-prem to cloud, which is what many organizations are looking to do these days – if they’re not already well into their migration journey, also means increased infrastructure costs, sometimes at twice as that of on prem.

In fact, to mitigate such increases, organizations – especially those dealing with high volumes, have started considering repatriating some of their data back to local infrastructure, and are now looking to implement a hybrid strategy.

Yet, regardless of the costs, management is still asking IT and data teams to collect more data (so they can dig deeper to get answers) and to deliver answers faster, regardless of where the data is (anywhere) and whatever format it’s in.

The importance of digging deeper and going faster with data anywhere cannot be understated. Every insight that is acted upon earlier contributes directly to both the top and bottom line – i.e., more revenues and lower operating costs.

We’ve even heard from our global customers that they have achieved savings by as much as millions of dollars by picking up on key strategic insights months before they used to be able to (before they could Ask Bigger).

How SQream makes it happen

What facilitates such impact is our ability to s on raw data efficiently and with without the need for preparation.

Such efficiency also means that a much smaller hardware footprint is required, which unlocks an additional and significant cost reduction as well as environmental benefits by lowering emissions.

As a hybrid solution, for both cloud and on prem, with SQreamDB you can analyze data where the cost-performance is optimized, for keeping some of your workloads on prem while reducing the cost of infrastructure.

On top of this, the data you do keep in the cloud can also be queried with fewer associated costs, by saving the time required for preparation and resource usage.

Not only does this approach bring unprecedented cost savings, it also enables the organization to expedite the extraction and implementation of insights from data, for impacting business performance.

For example, the sooner you can implement a new AI model the sooner you can improve engagement and conversion rates with a new lead generation campaign. Namely, you can identify and target prospects who are most likely to convert with the messages that are most likely to resonate with those personas, and bring in more leads and sales, faster.

The bottom line (and top line)

In summary, the value of Asking Bigger questions from big data is strategic to the health and growth of any business. To Ask Bigger, you need to dig deeper, go faster, and reach anywhere. With SQream this is exactly what you will do – not only assuring cost reductions on data-related expenditures, such as hardware (servers, multiple CPUs, storage), real estate (with less needed for less hardware), talent (with fewer IT resources required), and cloud services (by running complex queries on-prem).

But you will also grow the top line (increasing revenues by tapping into previously untapped opportunities) in addition to the bottom line (vis-à-vis operational savings).

Are you ready to Ask Bigger? Reach out to us and we’ll help you get started