Skip to main content

Home/ BI-TAGS/ Group items tagged cloud

Rss Feed Group items tagged

Filter: All | Bookmarks | Topics Simple Middle
cezarovidiu

2013 ERP research: Compelling advice for the CFO : Enterprise Irregulars - 0 views

www.enterpriseirregulars.com/...-compelling-advice-for-the-cfo

erp research

shared by cezarovidiu on 27 Feb 13 - No Cached
  • ERP vendor selection. As the following graph shows, the primary candidates for ERP software were SAP, Oracle, Microsoft, Epicor, and Infor:
  • The cloud question. Despite the hype, only 14 percent of respondents are using ERP delivered as Software as a Service (SaaS). Although the best cloud vendors can deliver superior security and reliability than most internal IT departments, market momentum to ERP in the cloud is not there yet, as the following diagram illustrates:
  • Important lessons. Implementing an ERP system is always complex because the deployment drives changes to both data and processes that extend across departmental boundaries inside the organization.
  • ...4 more annotations...
  • Software projects aren’t just technical endeavors. They’re also political, financial, emotional, structural, strategic, process and people-centric initiatives. Ignoring any one of these dimensions is done at the project manager’s peril.
  • Today’s CFO must balance the demands of two competing forces: the extraordinary wave of innovation (and the process changes these bring) against the regulatory, control-driven forces who want every process, every exception, and device to be documented, controlled and secured. In recent years, CFOs have spent tens of billions of dollars (or more) with audit firms to document the control points and risks within their existing ERP solutions.
  • ERP can bring significant benefit but implementation requires careful attention to both business planning and technology activities. For this reason, achieving project success and business value demand that CFO and CIO work together as a collaborative unit.
  • Therefore, it is essential to create this partnership and show your entire organization that the business and technology teams can communicate, collaborate, and share knowledge on a systematic and consistent basis. This collaboration is the true underlying strategy for gaining maximum value from ERP or any other enterprise initiative.
cezarovidiu

Why Soft Skills Matter in Data Science - 0 views

data-informed.com/oft-skills-matter-data-science

bigdata data science

shared by cezarovidiu on 24 Jan 14 - No Cached
  • You cannot accept problems as handed to you in the business environment. Never allow yourself to be the analyst to whom problems are “thrown over the fence.” Engage with the people whose challenges you’re tackling to make sure you’re solving the right problem. Learn the business’s processes and the data that’s generated and saved. Learn how folks are handling the problem now, and what metrics they use (or ignore) to gauge success.
  • Solve the correct, yet often misrepresented, problem. This is something no mathematical model will ever say to you. No mathematical model can ever say, “Hey, good job formulating this optimization model, but I think you should take a step back and change your business a little instead.” And that leads me to my next point: Learn how to communicate.
  • In today’s business environment, it is often unacceptable to be skilled at only one thing. Data scientists are expected to be polyglots who understand math, code, and the plain-speak (or sports analogy-ridden speak . . . ugh) of business. And the only way to get good at speaking to other folks, just like the only way to get good at math, is through practice.
  • ...4 more annotations...
  • Beware the Three-Headed Geek-Monster: Tools, Performance, and Mathematical Perfection Many things can sabotage the use of analytics within the workplace. Politics and infighting perhaps; a bad experience from a previous “enterprise, business intelligence, cloud dashboard” project; or peers who don’t want their “dark art” optimized or automated for fear that their jobs will become redundant.
  • Not all hurdles are within your control as an analytics professional. But some are. There are three primary ways I see analytics folks sabotage their own work: overly complex modeling, tool obsession, and fixation on performance.
  • In other words, work with the rest of your organization to do better business, not to do data science for its own sake.
  • Data Smart: Using Data Science to Transform Information into Insight by John W. Foreman. Copyright © 2013.
cezarovidiu

binami - 0 views

bitnami.com/stacks

cloud bitnami

shared by cezarovidiu on 14 Nov 14 - No Cached
1 - 8 of 8
Showing 20▼ items per page