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Archive for the ‘Business Intelligence’ Category


When a technical term is used more and more frequently the exact definition becomes “blurred” and its true meaning is usually greatly distorted.

This what happened to the term ‘business intelligence’ or BI. Ever since, when the term had only appeared, the development of technologies has substantially expanded our understanding of BI and of what advantage and benefit the company can retrieve from their available data.

So, what does ‘business intelligence’ mean today? How it could be useful for companies and how to apply its underlying ideas correctly to ensure the steady growth of efficiency and profitability of a business?

What is business intelligence? Why is it important?

BI consists of two completely diverse, but at the same time complementing one another aspects.

  1. Value for the business.

    Implies how companies can use the available information in order to multiply profit and efficiency and bring new products and services to the market successfully.

  2. IT strategy.

    Includes the idea of what technological solutions to apply in order to achieve greatest possible utility of BI.
    Presentation of data in a specific format for efficient usage by the company has always been a challenging task. For many organizations, it is quite complex to determine what particular information is required for a specific use.

Such business analysis requires certainty in methodologies and goals.

Earlier BI resources were limited by the lack of available data collection technologies. Nevertheless, modern technologies such as big data, analytics, mobile services and cloud computing in their combination allow obtaining a continuous flow of detailed information quite fast and with no serious investments.

Still, the current bottom line lies in extracting some valuable sense from these data and, in many respects, it is much more complicated than collecting information itself.

Five efficiency criteria of BI-system (and BI-strategy)

1. While selecting a BI-system one should be guided by the real needs of a particular company

The most common and at the same time the most dangerous mistake is when the BI-systems dictate the strategy of their usage. As a result, the company gets plenty of non-synchronized applications, awkward interface and the infrastructure that is already out of date, yet so entrenched in the IT system that could be barely substituted.

2. Be flexible

Flexible model of the integration of the appropriate software involves constant repetition of certain operations with the gradual development of the system. This allows companies to evaluate the success of the project at any point of time, to determine at what stage it is and towards what it moves.

As a rule, creating, testing and integration of BI-technologies goes much more smoothly when the company receives real-time feedbacks from all the running processes and is able to make required adjustments on the fly. It is vital for BI-systems!

3. User-friendly interface

BI-solutions focus on collection, visualization and management of the data.
Usually, when it comes to large amounts of numeric information companies face a risk to get exceptionally technical, inconvenient and incomprehensible data for the “illiterate” users of the system. This information is highly functional, but impractical, especially when it is badly integrated with other applications.

Integration is a key point in deploying BI-technologies. In case the interface is non-intuitive, complex and inconvenient for the end users, BI-system will definitely work inefficiently.

There is a tendency to allocate significant resources for the integration of the latest technologies promising unprecedented results. However, such investments potentially may do more harm than good. Intelligent, targeted and smooth integration is the key to avoid serious errors during implementation.

4. BI is a tool available to everyone

BI has been long used by completely different users, not only by experts with appropriate education and experience. BI-system should be simple and easy to understand to everyone.

For this purpose, companies have to attain the convenience of analytics and the reports drawn on its basis; it should be simple and demonstrative. The collected data should be presented in the way so that any user could easily make definite conclusions.

5. Centralize your data

The desire to achieve the result, based on useful information implies proper data handling. Receiving data from multiple sources and storing it in a centralized information DB, capable of filtering, sorting and removing the unnecessary is critical for the deployment of the applications involved into making business decisions. Apart from that, risk management also becomes more effective through transparency and structure.

General excitement over BI is evident

The role that IT plays in the world has significantly changed over the past few years thanks to the information ‘boom’. Still, construction of a technological infrastructure is not enough for successful data management.

That is why, ‘business intelligence’ it is not just a fashionable term it is a concept that demonstrates the need to move beyond the paradigm of a separate, isolated existence of data analysis and business goals.

In fact, BI reminds us that technologies and business must be closely linked, so that the business goals and business guidelines predetermine the choice of software and, the software in return would provide useful information leading business to success.


Ogneva Tatyana

Tatyana Ogneva

Business Development Manager

Skype: ognewatatyana
LI Profile: Tatyana Ogneva



Altabel Group

Professional Software Development



In today’s business and technology world you can’t have a conversation without touching upon the issue of big data. Some would say big data is a buzzword and the topic is not new at all. Still from my point of view recently, for the last two-three years, the reality around the data has been changing considerably and so it makes sense to discuss big data so hotly. And the figures prove it.

IBM reports we create 2.5 quintillion bytes of data every day. In 2011 our global output of data was estimated at 1.8 billion terabytes. What impresses it that 90 percent of the data in the world today was created in the past two years according to Big Blue. In the information century those who own the data and can analyze it properly and then use it for decision-making purpose will definitely rule the world. But if you don’t have the tools to manage and perform analytics on that never-ending flood of data, it’s essentially garbage.

Big data is not really a new technology, but a term used for a handful of technologies: analytics, in-memory databases, NoSQL databases, Hadoop. They are sometimes used together, sometimes not. While some of these technologies have been around for a decade or more, a lot of pieces are coming together to make big data the hot thing.

Big data is so hot and is changing things for the following reasons:
– It can handle massive amounts of all sorts of information, from structured, machine-friendly information in rows and columns toward the more human-friendly, unstructured data from sensors, transaction records, images, audios and videos, social media posts, logs, wikis, e-mails and documents,
– It works fast, almost instantly,
– It is affordable because it uses ordinary low-cost hardware.


Big data is possible now because other technologies are fueling it:
-Cloud provides affordable access to a massive amount of computing power and to loads of storage: you don’t have to buy a mainframe and a data center, and pay just for what you use.
-Social media allows everyone to create and consume a lot of interesting data.
-Smartphones with GPS offer lots of new insights into what people are doing and where.
-Broadband wireless networks mean people can stay connected almost everywhere and all the time.


The majority of organizations today are making the transition to a data-driven culture that leverages data and analytics to increase revenue and improve efficiency. For this a complex approach should be taken, so called MORE approach as Avanade recommends:
-Merge: to squeeze the value out of your data, you need to merge data from multiple sources, like structured data from your CRM and unstructured data from social news feeds to gain a more holistic view on the point. The challenge here is in understanding which data to bring together to provide the actionable intelligence.
-Optimize: not all data is good data, and if you start with bad data, with data-driven approach you’ll just be making bad decisions faster. You should identify, select and capture the optimal data set to make the decisions. This involves framing the right questions and utilizing the right tools and processes.
-Respond: just having data does mean acting on it. You need to have the proper reporting tools in place to surface the right information to the people who need it, and those people then need the processes and tools to take action on their insights.
-Empower: data can’t be locked in silos, and you need to train your staff to recognize and act on big data insights.

And what is big data for your company? Why do you use it? And how do you approach a data-driven decision-making model in your organization?

Would be interesting to hear your point.

Helen Boyarchuk

Helen Boyarchuk
Skype ID: helen_boyarchuk
Business Development Manager (LI page)
Altabel Group – Professional Software Development

I guess you have already read/heard a lot about CRM and BI, so in this article you will not find description what BI and CRM is. Also you will not find such dispute as “CRM vs BI” or “Why BI is not CRM” etc. What, then, is to discuss?🙂

Let’s imagine BI and CRM in its tandem.

The discipline of business intelligence includes a broad range of functional activities from data mining and statistical analysis to predictive modeling and reporting. So, BI-applications are often positioned as an indispensable tool for decision making at the tactical and strategic levels. As a rule in this case to work with information efficiently we will need enterprise data warehouse, building of which could “seed” at least half of the total budget for BI, in addition analytical models are rather expensive. Under these circumstances, the need of significant investment is one of the most essential and restrictive factors of dissemination of Business Intelligence systems. At the same time, experience shows that the usage of BI-applications can be fully justified at the operational level, where decisions must be taken exactly in real time. In this approach, building corporate Data Warehouse is not critical, and the using of pre-configured models is not necessary, because BI allows to implement arbitrary “point” data depending on the situation. If you don’t mind I would like to illustrate it with a concrete example.

Let’s consider a small example. For CRM-system we will take Oracle Siebel CRM, as for BI-application it will be Oracle BI. To implement CRM for realizing sms-mailing was proposed to use a single sms-gateway. Let’s assume that the frequency of such mailing is quite high, and volume is measured in ten of thousand of sms. Taking into account that the sms-gateway is just a tool of message transfering, you need to monitor constantly the process of mailing considering the timeline plan, “black lists”, the spam load per user, etc. In this case, in spite of the high performance of Oracle Siebel CRM,it is unreasonable to exchange data between the CRM-system and sms-gateway in online, but it`s reasonable to use additional transit system, which would redistribute the load. When you run a marketing campaign such a system would import data from Oracle Siebel CRM and after the campaign would pass results to the CRM-system . But, at the same time, in case any error arise or a failure campaign reaction time for the problem is reduced, you will know this only after the campaign ends and it may adversely affect the relationship with the client. You could solve this problem either using an expensive integration or through the using of BI-application. For example, Oracle BI enables to control the process of distribution and evaluate the results based on the data from the three systems online. Thus, in case of a large number of notifications incoming to the sms-gateway, that a message is not delivered to the recipient, it would be possible to stop the campaign quickly and make changes promptly, rather than waiting for its completion. Furthermore, using BI in this situation allows to correct the results during the campaign.

So the best effect in the marketing process could be obtained from using BI-applications at the operating level. Also effective BI-applications could be demonstrated in other CRM-processes. In sales BI-applications are indispensable in launching new products to market. In the service – when analyzing satisfaction, assessing value of each customer, etc.

In addition, I would like to notice that such tools as Oracle BI enable to cover the problem of business intelligence at the tactical and strategic levels of management effectively. In this case, using of a single tool would provide high-quality synchronization of business goals, set before BI. The previous experience guarantees more effective using of the already proven BI-application.

Thank you so much for your attention and hope this article is of interest to you.

Kind regards,
Elvira Golyak – Business Development Manager (LI page) | Skype ID: elviragolyak
Altabel Group – Professional Software Development

There is no doubt that 2012 will be another big year for BI and information management. In the article we`ve tried to gather what we suppose are the top BI trends for near future

Big Data → Need for Speed

The rise in volume (amount of data), velocity (speed of data) and variety (range of data) gives way to new architectures that no longer only collect and store but actually use data: on-demand or real-time BI architectures will replaces traditional datawarehouses. Successful business intelligence projects will need to consider Big Data as part of their data landscape for the value that it delivers. More and more organizations will look toward statistics and data mining to set strategic direction and gain greater insights to stay ahead of the pack.At the same time the BI user is expecting faster answers from their BI environment disregarding the fact that the size of data is increasing.

Shift from analytical BI to operational BI

Increased adoption of cloud and mobile BI encourage individuals to access their KPI dashboards (key performance indicators), more often. An operational dashboard works much like a car’s dashboard. As you drive, you monitor metrics that indicate the current performance of your vehicle and make adjustments accordingly. When the speed-limit changes, you check your speedometer and slow down, or when you see you are out of gas you pull over and fill-up. Likewise, an operational dashboard allows you to make tactical decisions based on current performance, whether it is chasing a red-hot lead or ordering an out-of-stock product.

Data democracy

Latest surveys showed that only 25% of employees in businesses that adopted BI had access to that tool. And that is not because they didn`t want to or didn`t need information, but because traditional BI tools have been too bulky and technical for that other 75% of employees to use.
As now organizations more and more are adopting cloud and mobile BI dashboards, this situation is likely to change. Business intelligence is heading towards simpler, more straightforward methods and tools..


An Agile approach can be used to incrementally remove operational costs and if deployed correctly, can return great benefits to any organization. Agile provides a streamlined framework for building business intelligence/data warehousing (BIDW) applications that regularly delivers faster results using just a quarter of the developer hours of a traditional waterfall approach.

It allows you to start a project after doing 20 per cent of the requirements and design that deliver 80 per cent of the project’s value. The remaining details are filled in once development is underway and everyone has a good look at what the challenges actually are.

BI going mobile

In a survey conducted by Gartner, it was found that by 2013 one-third of all BI usage will be on a mobile device, such as a smart-phone or tablet. BI users want to access their data anytime and anywhere. This puts a demand on both the backend of any BI solution (like datawarehouse appliances) but also on the frontend where information access and visualization must be possible.

BI going up to the Cloud

As Cloud computing continues to dominate the whole IT landscape, so BI also dominates in the Cloud . Throughout next few years adoption of cloud BI tools will be driven by a number of important factors. First, cloud-based solutions offer the advantage of being relatively simple and convenient to deploy. Second, cloud tools are more easily scalable to provide access to key performance indicators (KPIs) to everyone in your organization, no matter where they are or what device they are using. Lastly, continually improving security measures will put to rest any reservations businesses have with storing their sensitive data in the cloud.

We believe these above enumerated areas will grow over the next few years. Organizations will embrace the Agile approach, utilizing new tools and technologies to decrease delivery times and demonstrate substantial business value. As we put more data into the Cloud, big data will become standard. Data itself will be delivered to satisfy the desires of users, so access from mobile devices will dominate desk-based consumption. The businesses that embrace these new business intelligence trends, and take steps to change and adapt the way data is hosted, analyzed, utilized and delivered, will be the ones that grow and prosper in the near future.

And what are your predictions for the big business intelligence trends in the next few years? Do you agree/disagree with our predictions?

Kind regards,
Anna Kozik – Business Development Manager (LI page)
Altabel Group – Professional Software Development

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