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Trends and Applications
It has never been easier for businesses to collect significant amounts of data about their customers, their business, and their operations. However, there must be proper processes and systems in place to streamline the approach of making sense of all this data. Otherwise, it can be a needle in a haystack type of situation, limited by time and bandwidth even though the answer is in there.
As part of Data Summit Connect 2020, Joe Hilger, COO and co-founder of Enterprise Knowledge, LLC, and Sara Nash, a technical analyst with the consultancy, presented a presented a pre-conference workshop on knowledge graphs, which are becoming an increasingly valuable tool that organizations are using to leverage the vast amounts of data they collect, store, and analyze.
Whether their strategy is acquiring new customers or building the profitability of existing customers, marketers need that holistic customer view. Since they are on the front line, making them an afterthought in the centralized data process will under-serve the enterprise.
At Data Summit Connect 2020, DataStax VP Bryan Kirschner discussed how to create value with data. Citing an article from The Economist, Kirschner noted that data is the world's most valuable resource, and data creates new rules for competition. This reality is changing how technologists and strategists think about orchestrating processes and tools as well as the priorities for all companies.
The outbreak of the coronavirus, and the global pandemic that has ensued, has pushed millions of workers across the globe to work from home. This sudden sea-change in connectivity models and workforce management has left some businesses facing technical difficulties, as IT teams struggle to support hundreds or even thousands of workers on existing network capacity.
DataOps has emerged as an agile methodology to improve the speed and accuracy of analytics through new data management practices and processes—from data quality and integration to model deployment and management. Traditional methodologies for handling data projects are too slow to handle the teams working with the technology. The DataOps Manifesto was created as a response, borrowing from the Agile Manifesto.
As hybrid cloud models evolve into the new standard for enterprise storage and the ability to quickly and easily extract value from digital assets becomes ever-more important, storage expertise remains critical. According to Gartner, by 2025, 40% of workloads will reside in the public cloud, 30% at the edge and 30% on-premise—compared to the 80% on-premise in 2019. However, storage managers must move beyond their traditional roles in response to this changing landscape—a challenge that many are embracing.
From data quality issues to architecting and optimizing models and data pipelines, there are many considerations to keep in mind with regard to machine learning. At Data Summit Connect, a free 3-day series of data-focused webinars, a session, titled "Unlocking the Power of Machine Learning," provided a close look at the challenges involved in using machine learning, as well as the enabling technologies, techniques, and applications required to achieve your goals. As part of the session, Rashmi Gupta, director data architecture, KPMG LLC, explained how to use tools for orchestration and version control to streamline datasets in a presentation, titled "Operationalizing of Machine Learning Data." Adding to the discussion, Andy Thurai, thought leader, blogger, and chief strategist at the Field CTO (thefieldcto.com), shared how infusing AI into operations can lead to improvements with his presentation, "AIOps the Savior for Digital Business Unplanned Outages."
Columns - Database Elaborations
An enterprise conceptual data model is often seen as a high mountain to be climbed, a journey that will last a lifetime. People have visions of 10 feet or more of wall in the corporate offices wallpapered with an entity relationship diagram [ERD] that has zillions of teeny, tiny boxes and more relationship lines than the combined lines of queuing patrons in all Disney Resorts, when full. In this context, an enterprise conceptual data model is a daunting task not to be taken lightly. But in today's world, that enterprise conceptual data model can simply be a list of subject areas.
Columns - DBA Corner
Both development and production database administration are required to support database applications. However, it is not usually necessary to have different DBA staffs to perform the different roles. Indeed, intimate knowledge of how a database application was developed can make it easier to support that application once it becomes operational in the production world. But the bottom line is this: You will need to define, plan for, and staff both development and production DBA roles in order to create useful database applications.
Columns - MongoDB Matters
This year, an in-person MongoDB World conference in New York City was inconceivable. With NYC and the world still in various levels of COVID-19 lockdown, MongoDB World was held in the cloud as a virtual event—MongoDB.Live—in the first week of June. Holding the annual conference in the cloud is quite apt in many ways.
Pick Cloud recently assisted All Vend in moving the corporation's D3 application from on-premise to cloud with ease. All Vend is a management company that uses a D3 based proprietary system to provide their clients with a single source to set up and manage subcontracts with service companies, mitigate customer service issues, monitor insurance coverages and, collect, reconcile, and generate monthly sales reports on the thousands of vending machines serving their clients.
As COVID-19 continues to make its way throughout the world, Rocket Software is offering users and partners a virtual way to continue getting acclimated to MultiValue tools and solutions. Rocket has created a virtual series of deep tech training to connect the dots to new technologies so people understand how it relates to cloud, containers, and more. Dubbed MultiValue University, the virtual program includes demonstrations, seminar type training, interactive Q&A, and exercise examples.