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Practic, avem de-a face cu coborârea din sferele abstracte a BI-ului tradiţional către „enterprise intelligence“; o formă de „democratizare“ a BI-ului a devenit accesibilă maselor de utilizatori finali, pe baza ideii că instrumentele specifice acestui concept (analiză, raportare, semnalare etc.) trebuie să permită şi să ofere suport pentru luarea deciziilor în timp real.

Potrivit specialiştilor, „mutaţia“ menţionată reprezintă o evoluţie naturală, realizată sub presiunea pieţei, care impune luarea tot mai rapidă a unor decizii din ce în ce mai complexe la nivelul managementului operaţional în mod cotidian. Este vorba, practic, de o reorientare a conceptului de BI, de la tradiţionalul „data-centric“ spre mai pragmaticul „process-centric“, menit să permită un răspuns mai agil la provocările din piaţă.

Astfel, aplicaţiile de BI operaţional nu mai sunt rezervate doar analiştilor de business din top management, ci sunt accesibile şi directorilor executivi, managerilor şi utilizatorilor finali cu putere decizională. Prin intermediul acestui nou concept, managerii departamentelor de vânzări şi staff-urile din centrele de suport beneficaiză de informaţii relaţionate cu lista de activităţi zilnice şi de workflow-uri şi ghiduri de analiză, care îi ajută să interpreteze şi să analizeze informaţiile pe baza cărora trebuie să ia deciziile.

Great design, high-quality code, strong business sponsorship, accurate requirements, good project management, and thorough testing are some of the obvious requirements for successful analytics systems.

As a professional in the field, you must be able to do these things well because they form the foundation of a good analytics implementation.

Successful analytics professionals should follow a set of guiding principles.

These are few of the benefits of implementing a good quality CRM All of your clients’ information is stored in one place, it’s easy to update and share with the whole team. Updates by colleagues should be saved immediately. Every member of your team will be able to see the exact point when your business last communicated with a client, and what the nature of that communication was. CRMs can give you instant metrics on various aspects of your business automatically.  Reports can be generated. These can also be used to forecast and plan for the future. You will be able to see the complete history of your company’s interaction with a client. Calendars and diaries can be integrated, relating important events or tasks with the relevant client.  Suitable times can be suggested to contact customers and set reminders.

Finding one system that will fit your needs in one package may not be possible, so be aware that you may need to customise it to fit into your company. There are infinite possibilities here so don’t get too carried away as costs will rise accordingly.

Ensure that the CRM works on mobile devices and can be accessed remotely. Employees aren’t necessarily sat at their desks when it needs to be used or updated. Real-time updates are necessary for ensuring that clients aren’t contacted twice with the exact same follow up.

1. Project Sponsorship and Governance 2. Project Management 3. Development Team (Core Team) 4. Extended Project Team

1. Project Sponsorship and Governance IT and the business should form a BI steering committee to sponsor and govern design, development, deployment, and ongoing support. It needs both the CIO and a business executive, such as CFO, COO, or a senior VP of marketing/sales to commit budget, time, and resources. The business sponsor needs the project to succeed. The CIO is committed to what is being built and how.

2. Project Management Project management includes managing daily tasks, reporting status, and communicating to the extended project team, steering committee, and affected business users. The project management team needs extensive business knowledge, BI expertise, DW architecture background, and people management, project management, and communications skills. The project management team includes three functions or members: Project development manager - Responsible for deliverables, managing team resources, monitoring tasks, reporting status, and communications. Requires a hands-on IT manager with a background in iterative development. Must understand the changes caused by this approach and the impact on the business, project resources, schedule and the trade-offs. Business advisor - Works within the sponsoring business organization. Responsible for the deliverables of the business resources on the project's extended team. Serves as the business advocate on the project team and the project advocate within the business community. Often, the business advocate is a project co-manager who defers to the IT project manager the daily IT tasks but oversees the budget and business deliverables. BI/DW project advisor - Has enough expertise with architectures and technologies to guides the project team on their use. Ensures that architecture, data models, databases, ETL code, and BI tools are all being used effectively and conform to best practices and standards.

You can’t learn data visualization by memorizing a set of rules. You must understand why things work the way they do.

you must be able to think statistically

This doesn’t mean that you must learn advanced mathematics, nor can you do this work merely by learning how to use software to calculate correlation coefficients and p-values.

What this means in practice is that when the BI Server component starts up, it creates and reserves a number of threads in advance, determined by a number of parameters including SERVER_THREAD_RANGE.

You can see these threads running and ready to perform tasks for the BI Server component by using a tool such as Process Explorer for Windows

Thinking it through a bit, any given single query is, to a certain extent, only really going to use a small part of the total amount of CPUs available on a server, because it’s not the BI Server that runs queries in parallel, it’s the underlying database. For example, a single analysis against a single Oracle Database datasource would only really need a single BI Server thread to handle the query request, but when the underlying database receives the query, it might use a large number of its CPUs to process the query, returning results back to the BI Server to then pass back to the Presentation Server for display to the user.

The best practice in business intelligence delivery is always to build a data warehouse.

Pure transactional reporting is problematic. There are, of course, the usual performance issues. Equally troublesome is the difficulty in distilling a physical model down to a format that is easy for business users to understand. Dimensional models are typically the way business users envision their business: simple, inclusive structures for each entity. The standard OLTP data model that takes two of the four walls in the conference room to display will never make sense to your average business user.

One of the most challenging aspects of performance tuning is knowing where to begin. To maximize Oracle® Business Intelligence Enterprise Edition performance, you need to monitor, analyze, and tune all the Fusion Middleware / BI components. This guide describes the tools that you can use to monitor performance and the techniques for optimizing the performance of Oracle® Business Intelligence Enterprise Edition components.

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.