Enabling the Third Wave of Analytics: Embedded BI Takes Center Stage

GoodData

Today’s data-savvy companies actively seek ways to enhance their approach to analytics and evolve out of the past.  While the first wave of BI involved static, rigid, IT-owned systems, and the second expanded the capabilities to a more business-facing analyst set, the third wave aims to infuse analytical activity into multiple layers of non-technical business roles.  As a key strategy to enable this third wave, companies today are exploring an embedded approach that places analytical activity directly in the context of everyday user applications, and the independent software vendors (ISVs) and enterprises providing those applications have taken notice of this trend.  Done efficiently, embedded analytics promotes faster deployment and pervasive usage of analytics for end-users while delivering a competitive advantage and the opportunity for new revenue streams for software vendors and enterprises.
Watch Now

Spotlight

Big Data Speed of Processing...

OTHER ON-DEMAND WEBINARS

Gain Context, Insight and Value from Big Content

OpenText

The Internet of Things, social media and enterprise content all have one thing in common: they generate vast quantities of data — ever-faster. So much so that picking out relevant information and assembling it into meaningful patterns is a tall order. These new data sources also present another challenge. They generate unstructured data - such as text and emojis - that don’t fit neatly into traditional database structures. This data can however hold valuable insights on important and hard-to-quantify concepts such as social sentiment.
Watch Now

Transforming the Database: Critical Innovations for Performance at Scale

Your team is serious about ensuring database performance at scale. But legacy NoSQL technology could be eroding the impact of your achievements. Following best practices for efficient data modeling, query optimization and observability is fundamental. But their power can be limited – or enhanced – by specific database capabilities. Often-overlooked database innovations can serve as a force multiplier, paving a much smoother path to speed at scale (e.g., millions of read/write operations and millisecond P99 response).
Watch Now

Everything Data Scientists Should Know About Organizing Data Lakes

simplilearn.com

The recent GDPR regulations have changed the way companies handle the data they collect and store, making it imperative for data scientists to explore innovative ways to crunch and catalog data while ensuring that the company adheres to these new rulings that seek to establish complete data security.Join Big Data Expert Ronald Van Loon, and Simplilearns Chief Product Officer Anand Narayanan in a live video chat to understand.
Watch Now

COMPETE WITH THE GIANTS 7 ELEMENTS OF A DATA STRATEGY

analytics8.com

For most companies, data is viewed as a problem instead of an asset. Data is often stuck in systems that dont talk to each other, manual processes affect data quality, and analytics tools arent providing clear insights. But those companies who use their data to drive business strategy are out-performing their competitors. To be more competitive in any industry, you must take advantage of the ever-growing amount of available data and that starts with a Data Strategy. A documented roadmap that clearly defines company goals and the specifics on how to get there will put you on the path towards data driven decision making.
Watch Now

Spotlight

Big Data Speed of Processing...

resources

resource image

whitePaper

resource image

whitePaper

resource image

whitePaper