Business analyst data analysis approaches. Business Intelligence. Business analysis systems: basic concepts and solutions. History and principles of web search ranking

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Business Intelligence, or BI, is a general term that includes a variety of software products and applications created to analyze the primary data of the organization.

Business analysis as an activity consists of several related processes:

• data mining (data mining),
• analytical processing in real time (online analytical processing),
• retrieving information from databases (querying),
• making report (reporting).

Companies use BI to make informed decisions, cut costs and find new business opportunities. BI is something more than ordinary corporate reporting or a set of tools for obtaining information from the accounting systems of an enterprise. CIOs use business intelligence to identify ineffective business processes that are ripe for overhaul.

Using modern business analysis tools, businessmen can start analyzing data on their own and not wait for the IT department to generate complex and confusing reports. This democratization of access to information enables users to back up their business decisions with real numbers, which would otherwise be based on intuition and chance.

Although BI systems are promising enough, their implementation can be difficult due to technical and “cultural” problems. Managers need to provide clear and consistent data to BI applications so that users can trust them.

Which companies use BI systems?

Restaurant chains (such as Hardee’s, Wendy’s, Ruby Tuesday, and T.G.I. Friday’s) are actively using business intelligence systems. BI is extremely useful for them to make strategic decisions. What new products to add to the menu, what dishes to exclude, what inefficient points to close, etc. They also use BI for tactical issues such as renegotiating contracts with product suppliers and identifying ways to improve ineffective processes. Because restaurant chains are highly focused on their internal business processes and because BI is central to controlling these processes, helping to manage enterprises, restaurants, among all industries, are part of an elite group of companies that really benefit from these systems.

Business intelligence is one of the key components of BI. This component is essential to the success of a company in any industry.

In the sector retail Wal-Mart uses data analysis and cluster analysis extensively to maintain its dominant position in the sector. Harrah’s has changed the fundamentals of its gambling competition policy, focusing on customer loyalty and service level analysis rather than maintaining a mega casino. Amazon and Yahoo are not just big web projects, they are heavily using business intelligence and a common test-and-understand approach to streamline their business processes. Capital One conducts over 30,000 experiments annually to identify target audience and evaluating credit card proposals.

Where or from whom should BI implementation start?

Overall employee engagement is vital to the success of BI projects, as everyone involved in the process must have full access to information in order to be able to change the way they work. BI projects should start with top management, and the next group of users should be salespeople. Their main responsibility is to increase sales, and wage often depends on how well they do it. Therefore, they will much more quickly accept any tool that can help them in their work, provided that this tool is easy to use and that they trust the information they receive with its help.

You can order your pilot project on the business analysis platform.

Using BI systems, employees adjust work on individual and group tasks, which leads to more effective work sales teams. When sales leaders see significant differences in the performance of several departments, they try to bring the "lagging" departments to the level at which the "leading" ones work.

Once you've implemented business intelligence across your sales teams, you can continue to deploy it in other departments in your organization. A positive salesperson experience will help other employees move to new technologies.

How to implement a BI system?

Before implementing a BI system, companies should analyze the mechanisms for making management decisions and understand what information managers need to make these decisions more informed and promptly. It is also advisable to analyze in what form managers prefer to receive information (as reports, graphs, online, in paper form). Clarification of these processes will show what information the company needs to receive, analyze and consolidate in its BI systems.

Good BI systems should provide users with context. It is not enough just to make reports on what the sales were like yesterday and what they were a year ago on the same day. The system should make it possible to understand what factors led to exactly this value of sales on one day and another - on the same day a year ago.

Like many IT projects, BI implementation will not pay off if users feel “threatened” or skeptical about this technology and, as a result, refuse to use it. BI, being implemented for "strategic" purposes, should, in theory, fundamentally change the functioning of the company and the decision-making process, so IT leaders need to carefully approach the opinions and reactions of users.

7 stages of launching BI systems

1. Make sure your data is correct (reliable and suitable for analysis).
2. Conduct comprehensive user training.
3. Implement the product as quickly as possible, getting used to using it already during implementation. Don't waste a lot of time developing “perfect” reports, as reports can be added as the system evolves and user needs. Generate reports that will provide maximum value quickly (users are at the highest level for these reports), and then adjust them.
4. Take an integrative approach to building your data warehouse. Make sure you don't lock yourself into a data strategy that doesn't work in the long run.
5. Before you start, be clear about your ROI. Identify the specific benefits you intend to achieve, and then check them against the actual results every quarter or every six months.
6. Focus on your business goals.
7. Don't buy analytics software because you think that you need it. Implement BI with the idea that there are metrics among your data that need to be obtained. At the same time, it is important to have at least a rough idea of ​​where exactly they can be.

What problems can arise?

The biggest obstacle to the success of BI systems is user resistance. Among others possible problems- the need to “sift through” large volumes of irrelevant information, as well as data of unsatisfactory quality.

The key to getting meaningful results from BI systems is standardized data. Data is a fundamental component of any BI system. Companies need to tidy up their data warehouses before they can start extracting the information they need and trusting the results. Without data standardization, there is a risk of incorrect results.

Another problem can be an incorrect understanding of the role of the analytical system. BI tools have become more flexible and user-friendly, but their primary role is still reporting. You shouldn't wait from them automated control business processes. However, certain changes in this direction, nevertheless, are outlined.

The third obstacle in transforming business processes using a BI system is the lack of understanding by companies of their own business processes. As a consequence, companies simply do not understand how these processes can be improved. If the process does not have a direct impact on profit or the company is not going to standardize processes in all its divisions, the implementation of a BI system may be ineffective. Companies need to understand all the activities and all the functions that make up a separate business process. It is also important to know how information and data is transferred through several different processes, and how data is transferred between business users, and how people use this data to carry out their tasks within specific process... If the goal is to optimize the work of employees, all this must be understood before starting a BI project.

Some of the benefits of using BI solutions

A large number of BI applications have helped companies more than recoup their investment. Business intelligence systems are used to explore ways to reduce costs, identify new business opportunities, visualize ERP data, and quickly respond to changing demand and optimize prices.

In addition to increasing the availability of data, BI can provide companies with more negotiation benefits by making it easier to assess supplier and customer relationships.

Within the enterprise, there are many opportunities to save money by optimizing business processes and the decision-making process in general. BI can effectively help improve these processes by shedding light on the failures that have been made in them. For example, employees at one company in Albuquerque used BI to identify ways to reduce mobile phone use, work in overtime and other ongoing costs, saving the organization $ 2 million over three years. Also, with the help of BI solutions, Toyota realized that it had twice overpaid its carriers for a total of $ 812,000 in 2000. Using BI systems to detect defects in business processes puts the company in a better position, giving a competitive advantage over companies that use BI is just to keep track of what's going on.

• Analyze how leaders make decisions.
• Think about what information managers need to optimize operational management decisions.
• Pay attention to data quality.
• Think about the performance metric that has greatest value for business.
• Provide context that influences your performance metric.

And remember, BI is more than decision support. Through advances in technology and the way IT leaders implement them, BI systems have the potential to transform organizations. CIOs who successfully use BI to improve business processes make a much more meaningful contribution to their organization, leaders implementing basic tools drawing up reports.

Based on materials from www.cio.com

Over the decades of working with large customers, Force has accumulated vast experience in the field of business analysis and is now actively developing big data technologies. Olga Gorchinskaya, Director for research projects and Head of Big Data "Force".

15.10.2015

Olga Gorchinskaya

In recent years, a generation of leaders has changed. New people came to the management of companies, who made their careers already in the era of informatization, and they are used to using computers, the Internet and mobile devices both in everyday life and for solving work problems.

CNews: To what extent are BI tools in demand? Russian companies? Are there any changes in the approach to business analysis: from "analytics in the style of Excel" to the use of analytical tools by top managers?

Olga Gorchinskaya:

Today, the need for business analysis tools is already quite high. They are used by large organizations in almost all sectors of the economy. Midsize and small businesses alike understand the benefits of moving from Excel to dedicated analytics solutions.

If we compare this situation with the one that was in the companies even five years ago, we will see significant progress. In recent years, a generation of leaders has changed. New people came to the management of companies, who made their careers already in the era of informatization, and they are used to using computers, the Internet and mobile devices both in everyday life and for solving work problems.

CNews: But there are no more projects?

Olga Gorchinskaya:

V recent times we note a slight decrease in the number of new large BI projects. First, the complex general economic and political situation plays a role. It is holding back the start of some projects related to the introduction of Western systems. Interest in solutions based on free software also delays the start of BI projects, since it requires a preliminary study of this software segment. Many open source analytics solutions are not mature enough to be used everywhere.

Secondly, there has already been a certain saturation of the market. Nowadays, there are not many organizations that do not use business analysis. And, apparently, the time of active growth in the implementation of large corporate analytical systems.

And, finally, it is important to note that now the customers are shifting their emphasis in the use of BI-tools, which is holding back the growth of the number of projects we are used to. The fact is that leading vendors - Oracle, IBM, SAP - base their BI solutions on the idea of ​​a single consistent logical data model, which means that before analyzing something, it is necessary to clearly define and agree on all concepts and indicators.

Together with the obvious advantages, this leads to a great dependence of business users on IT specialists: if it is necessary to include some new data in the scope of consideration, the business has to constantly turn to IT to load data, harmonize it with existing structures, include it in the general model, etc. etc. Now we see that business wants more freedom, and for the sake of being able to add new structures on their own, interpret and analyze them at their own discretion, users are ready to sacrifice some part of corporate consistency.

So now the focus is on lightweight tools that allow end users to work directly with the data without worrying much about corporate consistency. As a result, we are seeing the successful advancement of Tableaux and Qlick, which allow us to work in the Data Discovery style, and some loss of market by large solution providers.

CNews: This explains why a number of organizations are implementing several BI systems - this is especially noticeable in the financial sector. But can such informatization be considered normal?

Olga Gorchinskaya

Today, tools that we once thought were too lightweight for corporate level... These are solutions of the Data Discovery class.

Olga Gorchinskaya:

Indeed, in practice, large organizations often use not a single, but several independent analytical systems, each with its own BI tools. The idea of ​​a corporate-wide analytical model turned out to be a kind of utopia, it is not so popular and even limits the promotion of analytical technologies, since in practice every department, or even an individual user, wants independence and freedom. There is nothing wrong with that. After all, in the same bank, risk professionals and marketers need completely different BI tools. Therefore, it is quite normal when a company chooses not a cumbersome single solution for all tasks, but several small systems that are most suitable for individual departments.

Today, tools that we previously thought were too lightweight for the enterprise level are taking the lead. These are solutions of the Data Discovery class. They are based on the idea of ​​simplicity of working with data, speed, flexibility and an easy-to-understand presentation of the analysis results. There is another reason for the growing popularity of such tools: companies are increasingly experiencing the need to work with information of a changing structure, generally unstructured, with a "blurry" meaning and not always clear value. In this case, more flexible tools are in demand than classic business analysis tools.

"Force" has created the largest in Europe and unique in Russia platform - Fors Solution Center. Its main task is to bring Newest technologies Oracle to the end customer, to help partners in their development and application, to make the equipment and software testing processes as accessible as possible. It is a kind of data center for testing systems and cloud solutions by partners.

CNews: How big data technologies are helping to develop business intelligence?

Olga Gorchinskaya:

These areas - big data and business intelligence - are moving closer to each other and, in my opinion, the line between them is already blurred. For example, deep analytics is considered “big data,” even though it existed before Big Data. Now interest in machine learning, statistics is increasing, and with the help of these big data technologies, it is possible to expand the functionality of a traditional business system focused on computing and visualization.

In addition, the concept of data warehouses has been expanded by the use of Hadoop technology, which has led to new standards for building enterprise storage in the form of data lakes.

CNews: For which most promising tasks are you using big data solutions?

Olga Gorchinskaya:

We use big data technologies in BI projects in several cases. The first is when it is necessary to improve the performance of the existing data warehouse, which is very important in an environment when companies are rapidly increasing the amount of information they use. Storing raw data in traditional relational databases is very expensive and requires more and more processing power. In such cases, it makes more sense to use Hadoop tooling, which is very efficient due to its very architecture, flexible, adaptable to specific needs and profitable from an economic point of view, since it is based on an Open Source solution.

With the help of Hadoop, we, in particular, solved the problem of storing and processing unstructured data in one large Russian bank... In this case, we were talking about large volumes of regularly arriving data with a changing structure. This information must be processed, disassembled, extracted from it numerical indicators, and also save the original data. Considering the significant increase in the volume of incoming information, using relational storage for this became too expensive and inefficient way. We created a separate Hadoop cluster for processing primary documents, the results of which are loaded into the relational storage for analysis and further use.

The second direction is the introduction of in-depth analytics tools to expand the functionality of the BI system. This is a very promising area, since it is associated not only with solving IT problems, but also with creating new business opportunities.

Instead of organizing special projects to implement in-depth analytics, we try to expand the scope of existing projects. For example, for almost any system useful function is the forecasting of indicators based on available historical data. This is not such an easy task, it requires not only skills in working with tools, but also a certain mathematical background, knowledge of statistics and econometrics.

Our company has a dedicated team of data analysts who meet these requirements. They carried out a project in the field of health care for the formation of regulatory reporting, and in addition, within the framework of this project, forecasting of workload was implemented medical organizations and their segmentation by statistical indicators. The value of such forecasts for the customer is clear, for him it is not just the use of some new exotic technology, but a completely natural expansion of analytical capabilities. As a result, interest in the development of the system is stimulated, and for us - new work. We are now implementing predictive analytics technologies in a project for city management in a similar way.

And finally, we have experience in implementing big data technologies where it comes to using unstructured data, primarily various text documents... The Internet offers great opportunities with its huge volumes of unstructured information containing useful information for business. We had a very interesting experience related to the development of a real estate appraisal system for ROSEKO on request Russian society appraisers. To select analog objects, the system collected data from sources on the Internet, processed this information using linguistic technologies and enriched it using geo-analytics using machine learning methods.

CNews: What own solutions "Force" is developing in the areas of business intelligence and big data?

Olga Gorchinskaya:

We have developed and are developing a special solution in the field of big data - ForSMedia. It is a social media data analysis platform for enriching customer knowledge. It can be used in various industries: financial sector, telecom, retail - wherever they want to know as much as possible about their customers.

Olga Gorchinskaya

We have developed and are developing a special solution in the field of big data - ForSMedia. It is a social media data analysis platform for enriching customer knowledge.

A typical use case is developing targeted marketing campaigns. If the company has 20 million customers, distribute all advertisements on the base is unrealistic. It is necessary to narrow the circle of ad recipients, and the objective function here is to increase customer response to the marketing proposal. In this case, we can upload basic data about all customers (names, surnames, dates of birth, place of residence) into ForSMedia, and then, based on information from social networks, add new useful information to them, including circle of interests, social status, family composition, professional area. activities, music preferences, etc. Of course, such knowledge can not be found for all clients, since a certain part of them do not use social networks at all, but for targeted marketing such an “incomplete” result gives huge advantages.

Social networks- a very rich source, although it is difficult to work with it. It is not easy to identify a person among users - people often use different shapes their names, do not indicate age, preferences, it is not easy to find out the characteristics of a user based on his posts, subscription groups.

The ForSMedia platform solves all these problems on the basis of big data technologies and allows enriching customer data and analyzing results on a massive scale. Technologies used include Hadoop, R statistical research framework, RCO linguistic processing tools, Data Discovery tools.

The ForSMedia platform makes the most of free distribution software and can be installed on any hardware platform that meets the requirements of a business task. But for large deployments and with increased performance requirements, we offer a special version optimized to work on Oracle hardware and software systems - Oracle Big Data Appliance and Oracle Exalytics.

The use of innovative integrated Oracle complexes in large projects is an important area of ​​our activity not only in the field of analytical systems. Such projects will turn out to be not cheap, but due to the scale of the tasks being solved, they fully justify themselves.

CNews: Can customers test these systems somehow before making a purchasing decision? Do you provide, for example, test benches?

Olga Gorchinskaya:

In this direction, we do not just provide test stands, but have created the largest in Europe and unique in Russia platform - Fors Solution Center. Its main task is to bring the latest Oracle technologies closer to the end customer, to help partners in their development and application, to make the equipment and software testing processes as accessible as possible. The idea did not arise out of nowhere. For almost 25 years, Force has been developing and implementing solutions based on Oracle technologies and platforms. We have extensive experience in working with both clients and partners. In fact, Force is the Oracle competence center in Russia.

Based on this experience, in 2011, when the first versions of the Oracle Exadata database engine appeared, we created the first laboratory for the development of these systems, called it ExaStudio. On its basis, dozens of companies could discover the possibilities of new Exadata software and hardware solutions. Finally, in 2014, we turned it into a kind of data center for testing systems and cloud solutions - this is the Fors Solution Center.

Now our Center presents a full line of the latest Oracle hardware and software systems - from Exadata and Exalogic to large machines Big data Data Appliance - which, in fact, act as test benches for our partners and customers. In addition to testing, here you can get services for auditing information systems, migrating to a new platform, setting up, configuring and scaling.

The center is actively developing in the direction of using cloud technologies. Not so long ago, the architecture of the Center was refined in such a way as to provide its computing resources and services in the cloud. Customers can now take advantage of the self-service performance capabilities of uploading test data, applications, and testing to the cloud.

As a result, the partner company or customer can download own applications to our cloud, test, compare performance results and make a decision about moving to a new platform.

CNews: And the last question - what will you present at Oracle Day?

Olga Gorchinskaya:

Oracle Day is the main event of the year in Russia for the corporation and all its partners. "Force" has repeatedly been its general sponsor, and this year too. The forum will be entirely devoted to cloud topics - PaaS, SaaS, IaaS, and will be held as Oracle Cloud Day, since Oracle pays great attention to these technologies.

At the event, we will present our ForSMedia platform, as well as talk about the experience of using big data technologies, about projects in the field of business intelligence. And, of course, we will tell you about the new capabilities of our Fors Solution Center in the field of building cloud solutions.

Small businesses in the CIS countries do not yet use data analysis for business development, determining correlations, searching for hidden patterns: entrepreneurs get by with the reports of marketers and accountants. Small and semi-medium-sized business leaders rely more on their intuition than on analysis. But at the same time, analytics have huge potential: it helps to reduce costs and increase profits, make decisions faster and more objectively, optimize processes, better understand customers and improve the product.

An accountant is not a substitute for an analyst

Small business leaders often assume that the reports of marketers and accountants adequately reflect the activities of the company. But it is very difficult to make a decision on the basis of dry statistics, and an error in calculations without specialized education is inevitable.

Case 1. Post-analysis of promotional campaigns. By the New Year, the entrepreneur announced a campaign, within the framework of which certain goods offered at a discount. After assessing the revenue for the New Year period, he saw the sales increase and was delighted with his resourcefulness. But let's take all the factors into account:

• Sales grow especially strongly on Friday, the day when revenue is highest - this is a weekly trend.
• Compared to the growth in sales that usually occurs under New Year, then the gain is not so great.
• If we filter out promotional items, it turns out that the sales figures have deteriorated.

Case 2. Research of turnover. At the store women's clothing difficulties with logistics: the goods are in short supply in some warehouses, and in some they have been lying for months. How to determine, without analyzing sales, how many trousers to bring to one region, and how many coats to send to another, while getting the maximum profit? To do this, you need to calculate the turnover, the ratio of the speed of sales and the average inventory for a certain period. Simply put, turnover is an indicator of how many days a store will take to sell a product, how quickly an average stock is sold, and how quickly a product pays for itself. It is economically unprofitable to store large reserves, as it freezes capital and slows down development. If the stock is reduced, there may be a shortage and the company will again lose profit. Where can you find the golden mean, the ratio at which the product does not stagnate in the warehouse, and at the same time, you can give a certain guarantee that the customer will find the desired unit in the store? To do this, the analyst should help you determine:

• desired turnover,
• turnover dynamics.

When settling with suppliers with a deferral, it is also necessary to calculate the ratio of the credit line and turnover. Turnover in days = Average commodity stock* number of days / turnover for this period.

Calculation of the remaining assortment and the total turnover by stores helps to understand where it is necessary to move a part of the product. It is also worth calculating what turnover is for each unit of the assortment in order to make a decision markdown with a reduced demand, additional order with an increased one, moving to another warehouse. By categories, you can develop a report on turnover in this form. It can be seen that T-shirts and jumpers are sold faster, but coats - for a long time. Will an ordinary accountant be able to do such work? We doubt it. At the same time, the regular calculation of turnover and the application of the results can increase profits by 8-10%

In what areas is data analysis applicable?

1. Sales. It is important to understand why sales are going well (or bad), what the dynamics are. To solve this problem, you need to research the factors influencing profit and revenue - for example, analyze the length of the check and the revenue per customer. Such factors can be investigated by product groups, seasons, stores. You can identify highs and sales pits by analyzing returns, cancellations, and other transactions.
2. Finance. Monitoring indicators is necessary for any financier to monitor cash flow and allocate assets across various areas of business. This helps to assess the efficiency of taxation and other parameters.
3. Marketing. Any marketing company needs predictions and post-stock analysis. At the stage of working out the idea, you need to determine the groups of goods (control and target) for which we are creating an offer. This is also a job for a data analyst, since an ordinary marketer does not have the necessary tools and skills for good analysis. For example, if for the control group the amount of revenue and the number of buyers is the same in comparison with the target, the action did not work. Interval analysis is needed to determine this.
4. Control. Leadership is not enough for a company leader. In any case, quantitative assessments of the work of personnel are necessary for the competent management of the enterprise. It is important to understand the efficiency of payroll management, the ratio of salaries and sales, as well as the efficiency of processes - for example, the workload of cash registers or the employment of loaders during the day. This helps to properly manage working hours.
5. Web analysis. The site needs to be properly promoted in order for it to become a sales channel, and this requires the right promotion strategy. This is where web analysis comes in. How to use it? Study the behavior, age, gender and other characteristics of customers, activity on certain pages, clicks, traffic channel, the effectiveness of mailings, etc. This will help improve your business and website.
6. Assortment management. ABC analysis is essential for assortment management. The analyst must distribute the product by characteristics in order to conduct this type of analysis and understand which product is the most profitable, which is the basis, and which one should get rid of. To understand the stability of sales, it is good to conduct an XYZ analysis.
7. Logistics. More understanding about procurement, goods, their storage and availability will be given by studying logistic indicators... Losses and needs of goods, inventory is also important to understand for successful business management.

These examples show how powerful data analysis can be, even for small businesses. An experienced director will increase the company's bottom line and benefit from the smallest information by using data analysis correctly, and the manager's job will be greatly simplified by visual reports.