When you are looking for more business insight it means that you are in need of more information and business numbers. Exactly this information comes from Big Data – the huge amounts of different data that is created by your company, customers and interactions every day. The volume of this data is getting bigger and bigger because of the social media, cloud technology and online consumer behavior. Look at such successful companies as Google, Amazon and Target that have been gathering data for years and agree that it is the best way to be competitive and win your market today. But there is a challenge – how is it possible to avoid getting by all ‘noise data’ and the irrelevant numbers that flow with the relevant and useful data?
A consultant and Forbes contributor, Paul Magone states that “Progressive firms use big data to narrow their decision set, not expect an answer” and adds “They have figure[d] out how to map the real-time information against historical information to offer predictive possibilities. The modern crystal ball is thus unveiled and companies await the next prediction.”
The specialist explains the success of business insight as these six issues:
- First of all you have to determine the vital questions: What issue will you clarify to truly move your business forward? You have to understand and be able to measure the business impact of analytics outcomes. The investments must be measured and the project must be provided with the tasks.
- Understand the key persons who will have the access to the data marts and analytic dashboards. The staff that involved in BI project must be limited and real professional in terms of understanding business process and security policy. The data is your key information and it should not lack to your competitors.
- Determine the gathered data as data at rest, data in motion and data in use. Is your data volatile and incomplete? You will find the right tools and methods when you will structure the gathered data.
- Try to target the needed data – social media, mobile devices, localization. It is better to set up some options before you start collecting data.
- Be sure that the data is put in context against business issues that matter.
- Determine the recommendations based in the data discovery and overall needs of the stakeholders.
Do not forget that Big Data may not give you the only right answer but it always narrows the range of possible answers and provide you with the right numbers.
Business Intelligence (BI) dashboards are the must-have control panels that help leverage gathered Data for busy business managers and workers who are not supposed to dig Big Data deeply. BI Dashboards are presented in charts, graphs, gauges, etc., the tools that are designed for the data analysis process. But there is another problem – how to build an effective dashboard that really works and suits to all executives and heads of business units? The challenge of IT department VS Business users could happen, since the last ones are the demanding audience with numbers in the heads.
Most likely you will not escape this issue except in the case when the dashboards are already the part of BI landscape. To understand the challenge of BI dashboards better let`s see the real stats of a survey. The consultancy of Dresner Advisory Services says that dashboards topped the list of technologies that expected to be most vital to BI strategies – this statement was made according to the answers of 859 BI and business specialists (2012). Forty one percent of the respondents stated that BI dashboards were critical to their data analysis process, while thirty seven percent estimated them as very important tools. But just 1% ranked the dashboards as not important at all.
The development of advanced data visualization capabilities adds new challenges for BI designers who must avoid overloading screens with flashy graphics that only get in decision-makers` way. Read more about BI dashboards and the implementation practices on datawarehousesoftware.org
Data mining is becoming the real must-have tool for every business that has already faced Big Data challenge and going to leverage this technology factor. Over the past decade, Data Mining has taken its shape and techniques so now it is not just a hot trend but a valid IT field that works with ROI and marketing improvements. In fact all of us are dealing with Data Mining tens of times a day from Social Media messages to the fraud-detection algorithms that scrutinize our every credit card purchase.
The popularity of Data Mining tools is very simple – it does work as for big businesses so for mid-market enterprises. Especially today, the technologies are getting cheaper and easier, so even mid-market companies with limited IT department can afford it. But even with all these benefits and wows not all the executives have the idea how to get started with Data Mining and Business Intelligence project.
Data Mining and BI project must begin with a plan of business opportunities. Simply, make a diagram with three phases of the DM/BI. In the 1st phase find out the requirements of gathering process – make a list of opportunities that will lead to a great business impact. The most important steps in Data mining are not about technology but about understanding the business and its approaches. Have a meeting with business-oriented people and decide what will be your high-level opportunities of Data Mining project. The 2nd phase of diagram should point out what are the demands and tasks that will help to reach these goals, also mention the business analysts who will manage the data. In the 3d phase you will identify the business goals that will be met with the Big Data and BI.
Since you have done your diagram, make a draft with these questions:
– Business opportunity description;
– Expected data issues;
– Modeling process description;
– Implementation plan;
– Maintenance plan.
The good business plan and the right people will lead to the success in implementation of Data Mining Project.
A recent survey (2013) has shown that the businesses are more and more interested in Big Data, Business Intelligence and the benefits of BI implementation. The survey is conducted by the Economist Intelligence Unit and contains 700 interviewed companies that share their opinion on Big Data – whether they use Big Data strategy or not. According to the interviews all the surveyed organization mark that they are facing the challenge of rising amounts of Big Data and there is a strong correlation between successful organizations and organizations that leverage Big Data and manage Business Intelligence projects. It is possible to say that companies that run business intelligence appear to be more intelligent and more competitive than their opponents.
Also, the survey shows that nearly 50 percent of respondents whose companies perform significantly greater than their peers have a well-defined Big Data strategy. All these market winners work with one data strategy plan – it is strongly recommended to determine the business goals and arrange the priority of them first, then find key persons with skills and experience who will manage the big data projects.
“An organization’s data is only as good as the business insights it reveals,” – states Paul Kent, vice president of big data at SAS. “Mapping your big data strategy to address your challenges is crucial. But the importance of hiring the right people to manage and analyze your data and communicate results cannot be overstated.”
As we can see, the nowadays business is in big need of Data scientists and data managers – the employees who will gain insight from data. These key persons will play key role in decision making and provide executives with vital business advices and reports. Also, 66 percent of respondents admit that they are gathering WEB data about their customers, 22 percent say that social media and WEB data improves their interactions with customers, while this number increases to 32 percent among most successful organizations.
The traditional meaning of Data warehouse that appeared in the late 70s is the end-to-end solution for business users. This is about extracting data and storing it into special data models, queries with the help of applications and reports. Then, in 90s appeared the concept of Business Intelligence that became a solution which represented the given data in dashboards, reports, scorecards and variable diagrams. So, the BI concept does not exist without Data warehouse, because Data warehouse is simply the foundation for BI. Nevertheless, with the quick development of IT and analytic tools, which are involved in the same business process, the people are using the terms in an interchangeable way. Sometimes data warehouse and business intelligence are recognized as the very same project.
It is better to make clear what really BI means before you start a new BI project. Business Intelligence has two dynamic terms: the way to model the business with BI tools, where the business evolves all the time responding to strategies and market conditions. These BI models give the valuable information to decision-making that helps to build numerous business scenarios. Business Intelligence means to learn about the business and face new questions that will arise. Another widely used description of BI is Business Insight – this meaning correctly describes BI for management use.
Also, it is important to understand that BI solution itself is not your key to all the “business doors” – it can provide you with the dashboards, graphs etc., but the real value comes after interaction of BI and decision-maker, a person who can leverage all the information and provide the system with right queries. Without this business logic, the BI tools can tell you only the things that you already know. That is why it is better to consider Business Intelligence as Business Insight instead of data storing, so that we can focus on the business value instead of the technological issue.
True Business Intelligence system has three key components:
- Focusing on business
- Structuring delivered data
- Strong analytic tools