Better Data Means Better Business Decisions

Data, the life blood of today's economy, is an attractive target for cyber attackers. Learn how a self-securing database provides security and peace of mind without relying on manual, error-prone processes allowing you to focus on innovation and not damage control.

Webinar will discuss about: History and present of SAP Business Model. Overview of Technology underlying SAP HANA (In Memory Computing) , Bigdata, Space for Analytics. SAP HANA Modelling Environment (Architecture + Setting up Environment). Data warehousing Models (Star schema + concept of master data). Basic Graphical Views (attribute, analytical and calculation Views). Data base operation in Hana tool.

Relational databases are old technology, right? Thirty years is a long time for a technology foundation to be as active as relational databases, but, like NFL coaches, we must “tolerate them until we can replace them.” Are their replacements here? In this webinar, we say no. Databases have not sat around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage options like a kid in a candy store? We’ll discuss Hadoop’s continued potential relevance and the cloud storage option that seems vital. Use what when? This is a critical decision that can dictate two to five times additional work effort if it’s a bad fit.

Modern-day systems are transforming into complex, open-source, cloud-native services running on various environments and being developed/deployed at lightning speed by distributed teams. When working on these systems, identifying a broken link in the chain can be near impossible. Everything fails at one point or another, whether due to code bugs, infrastructure overload, or changes in end-user behavior or market driven factors or errors in data collection. This has led to the rise of DataOps with a focus on changing the organizational speed and trust in delivering data pipelines and the related artifacts by co-creating “decision quality” data with the consumers. This development has led to the idea of observability that includes monitoring, tracking, and triaging incidents to prevent downtime of the systems and around several factors such as freshness, distribution, volume, schema, lineage.