Analytics

Gartner predicts that by 2023, organizations that promote data sharing will outperform their peers on most business value metrics. According to Debra Logan, Gartner’s Research Vice President, “Data sharing is the way to optimize higher quality data and more robust data and analytics to solve business challenges and goals.” Given these numbers, it is clear that businesses will need to embrace application software integration as a core business strategy.

MongoDB vs DynamoDB: How do you choose between them? Whether you are a two-man team bootstrapping a proof of concept or an established one battling with high throughput and heavy load; this post can serve as a guidepost in your decision process. Before going into the details, a brief history lesson on how these technologies emerged is pertinent; you must understand the optimal conditions for running these systems and how they operate in the wild before making an informed choice.

According to Gartner, leading organizations in every industry are wielding data and analytics as competitive weapons. Companies that leverage data as a competitive differentiator will stand the best chance of acting faster on opportunities and responding to threats in a competitive marketplace. The problem is that most companies aren’t aware of the value of their data. As a result, they aren’t leveraging the full potential of their data to make informed decisions.

Advertising agencies are faced with the challenge of providing the precision data that marketers require to make better decisions at a time when customers’ digital footprints are rapidly changing. They need to transform customer information and real-time data into actionable insights to inform clients what to execute to ensure the highest campaign performance.

The CDP Operational Database (COD) builds on the foundation of existing operational database capabilities that were available with Apache HBase and/or Apache Phoenix in legacy CDH and HDP deployments.

From cost estimates and project ROI to schedule variance and task completion rates, project managers share the top KPIs they are monitoring.

Sometime in 2019, Netflix cracked a conundrum that stumped them for years. The company had so much data about its content and subscribers, it had to sync multiple heterogeneous data stores like MySQL and Elasticsearch continuously, which brought seriously stressful challenges like dual writes and distributed transactions. So Netflix created its own CDC tool that processes captured log events in sequence and takes dumps for specific tables and primary keys of tables. Problem sorted. Case closed.

Spark is known for being extremely difficult to debug. But this is not all Spark’s fault. Problems in running a Spark job can be the result of problems with the infrastructure Spark is running on, inappropriate configuration of Spark, Spark issues, the currently running Spark job, other Spark jobs running at the same time – or interactions among these layers.

Imagine this: less than half an organization’s structured data is used in decision-making. Think of the missed opportunities for customer acquisition and revenue by not taking advantage of that information. According to an IBM study, 87 percent of CEOs regard data as a strategic asset. So why then are companies not harnessing the power of this information?

When I started out in my career, it was very much all about the numbers, and thinking, not feeling, when it came to communicating important results found in business data.