Systems | Development | Analytics | API | Testing

OKRs have taken corporate planning by storm — and for good reason. As a system for organization-wide goal-setting, OKRs make executive KPIs tangible and actionable, not just for the leaders, but for everyone in the company. They have become increasingly common in all types of businesses because they are simple and effective. For the company’s data champion, they also offer an unparalleled opportunity to get everyone speaking a common language of metrics.

As businesses scale to meet the demands of their customers, so do their need for efficient products to collect, manage and analyze data to meet their business goals. Whether you are building a multi-player game or a global e-commerce platform, it's critical to ensure that data can be stored and queried at scale with strong consistency and then processed for analysis to deliver real-time insights.

Geographical data is one of the critical datasets for data-driven organizations to make informed business decisions. As the data is growing more than ever before, it’s becoming more challenging to manage and analyze mammoth datasets using traditional databases, this is true for geographical data as well as it requires significant computational power to process. Esri has been one of the leading companies in Geospatial software development since 1969.

Development time is precious. Developers are highly-skilled and highly-paid, and so naturally you want to make sure that they are as productive as possible. Many organizations are starting to hire Developer Experience Engineers to make sure that their developers are using the best tools and processes possible. To make developers more productive, the first step is to figure out exactly what developers are actually doing. Then, we need to figure out what we want them to do.

Enterprises are spending more and more of their budgets on technologies and IT infrastructure as they invest in digital transformation. As a result, the “digital economy” — a term used to describe all the economic activity that results from digital technology spending — accounts for 9.6 percent of U.S. GDP, according to the latest statistics. But what is the digital economy, and what are the processes underpinning it?

Any software application must work properly, generate the right results, satisfy stakeholders, and fit into the organization's overall objectives. Automated testing can help. It may sound easy, but we all know that achieving all of the above takes a lot of effort. Can we take a shortcut without compromising quality or causing costs to explode?

Amazon Redshift is one of the world’s most popular cloud data warehousing solutions. Along with other Amazon Web Services offerings, such as Amazon S3 and Amazon EMR (Elastic MapReduce), Redshift can help enhance your data workflows and manage your enterprise data. With the right expertise, Redshift can help you integrate all of your data sources, from operational databases and data lakes to third-party files and websites.

Here are five key takeaways about data mining: Data mining techniques draw from a wide range of subjects, from database management to machine learning and everything in between. In this article, updated for 2022, we discuss the most important data mining techniques and how to employ them to maximize your data investments.

The word “isolate” shouldn’t be new to you — since the pandemic started, it has become a buzzword. Chances are you’ve also heard the term used in relation to Flutter, but what exactly is an isolate in this context? How does Dart execute code? How do you implement a isolate? All these questions will be answered in this article. If you’re a beginner in Flutter development, this article is for you, as I’ve tried to simplify a lot of concepts.

Still waiting for ML training to be over? Tired of running experiments manually? Not sure how to reproduce results? Wasting too much of your time on devops and data wrangling? Spending lots of time tinkering around with data science is okay if you’re a hobbyist, but data science models are meant to be incorporated into real business applications. Businesses won’t invest in data science if they don’t see a positive ROI.