So far in this series, we’ve been focused on generic concepts and console-based workflows. However, when you’re working with huge amounts of data or surfacing information to lots of different stakeholders, leveraging BigQuery programmatically becomes essential. In today’s post, we’re going to take a tour of BigQuery’s API landscape - so you can better understand what each API does and what types of workflows you can automate with it.

If the COVID-19 pandemic has taught us anything, it is that speed and intelligence are of the essence when it comes to making business decisions. Organizations must find ways of keeping ahead of competitors and disruptions by continually leveraging data to make smart decisions. The problem? Data may be everywhere, but it’s not always available in a form that businesses can use to generate analytics in real time.

Look around and you’ll see the benefits of hyperautomation everywhere as it scales business processes faster than a speeding algorithm, takes the friction out of customer engagement, and drives business transformation to the moon and back. In the long run, this trend will likely create a new generation of jobs. But in the short term, it may also raise anxiety among workers fearing job loss amid the post-COVID hyperautomation boom. To put this anxiety into perspective.

Businesses are flooded with constantly changing thresholds brought on by seasonality, special promotions and changes in consumer habits. Manual monitoring with static thresholds can’t account for events that do not occur in a regularly timed pattern. That’s why historical context of influencing events is critical in preventing false positives, wasted resources and disappointed customers.

See how the Logit.io platform helped give Youredi a more streamlined reporting and data visualisation alternative to using Microsoft’s Power BI in our latest customer case study. Outside of its BI capabilities, the Logit.io platform is used throughout Youredi by everyone from their technical teams through to their customer support and professional services department.

One of the most important things to consider is the cost of the platform coupled with the cost of the integration. Now that we have understood what NetSuite integration is, some of the drawbacks, and why you should consider an integration, we are going to delve into how to do the integration itself. The approach you are going to take to do the integration is determined by the technical expertise if any, the application to be connected with NetSuite, and your budget.

As enterprises seek to accelerate the process of getting insights from their data, they face numerous sources of friction. Data sprawl across silos, diverse formats, the explosion of data volumes, and the fact that data is spread across many data centers and clouds and processed by many disparate tools, all act to slow the progress.

While the AI and automation capabilities of augmented analytics dominate today’s business intelligence (BI) conversations, data storytelling is fast becoming a hot topic - and together, they’re set to re-shape the future of BI.

WIth Databox, Digital22 got a solution that enabled them to spend less time on reporting while continuing to offer clients transparency, along with the custom metrics they really care about.

Developing against third-party or unfamiliar web APIs can be painful and slow compared to using native libraries. For example, making requests with an HTTP client is simple enough but offers no compile-time sanity checks and no way for code suggestion tools like Intellisense to help you navigate. Worst of all, if the API you are consuming introduces breaking changes, you won’t find out until runtime.