This article is
A Small Story about our situation before I proceed to the main context! There is not affordable money for marketing this month and we left out with very smaller budget comparing past monthly budget. But we still hold the responsibility for the company to hit the target for this Month That’s a challenge!
So I have been thinking a lot for an Idea, Strategy to achieve the forecast number without a spending much money and the answer looks like
- Focus on existing customer by communicate with them through low cost channel and efficiently
- Analyze them deeply this time than ever & tailor the content for them
The above was the only plan blinking in my mind for now. So understanding that I need to analyze my customers and think differently, the only resource is past data of those user’s behaviors. So I begin analyzing data and there was honest thinking
“You are not Data Scientist or Master of Data Analyze and… you going to do the same way how you do in the past. Hmmm… I need to do it like master” So was digging the topic on data analyze by Googling and the result is Wikipedia.
Lets stop the story for few minutes. It started like the below.Data analyze (understand the basic first)
Under Data Analyze, there are different terms with slightly different meaning,
- Data Mining: Particular data analysis technique focused on
modellingand knowledge discovery of Predictive http://wikipedia.org/wiki/Data_mining
- Business Intelligence: Cover data analysis by relies heavily on aggregation & Focused on business Information http://wikipedia.org/wiki/Business_intelligence
- Statistical Analysis has 3 Types:
- Descriptive Statistics
- Exploratory Data analyze(EDA): Focused on discovering new features in the data
- Confirmatory Data Analyze(CDA): Is confirming or Falsifying existing hypothesis
- Predictive Analytics: Focused on Statistical or structural model for predictive forecasting or classification of data
So was clear about the definition and basics before researching deeply and concluded that I need to digg more on Business Intelligence to find opportunities through business information. I started Googling again about BI, Luckily got a very insighful article named “BI 2.0 for the CIO – Chief Intelligence Office” from Analytics8.com.
Below the Lessons learned from Analytics8.com about Business Intelligence:
This article is short briefing on the latest tools and technologies in BI (I mixed up the article with my situations)
“Business Intelligence is a collection of tools and techniques to provide an experience that gets the right information into the hands of the people who need it in whatever the format they want in, and as quickly as they can ask the question.” – Analytics8.com
We need to connect the below and provide an experience to the people:
- Cloud BI
- Mobile BI
- Data Discovery
- Big Data
The article start by advising that organization needs to builds solid data infrastructure could be key for the long-term ability to react quickly to the fast-changing data needs for organization.
The Problem: (why it is important?)
Every organization need a solid data infrastructure, So the data could be available to all users in an organization and the most demanding users (Organization people) will often need more information, ignoring the most demanding info is a big mistake. (I experienced people used to get disappointment with this kind of situation and everyone need to depend on IT-Dept for the information)
Hence building a solid data infrastructure can help business users to do it (or try to do it) with or without the blessing of IT.
So what was blocking business to achieve this? The barrier is building comprehensive data warehouses is time consuming and costly. But in recent years, the technology is breaking down the time and cost barrier. Options like SAAS or cloud based data warehouse reduces the cost, Also mobile BI and data discovery tools provide more value to business more quickly than ever.
So why the companies is not starting the process to achieve this? Once build a data warehouse, maintaining it can be a challenge as often data warehouses turn into “data landfills” with conflicting data and little institutional knowledge of the data in the warehouse.
So what we can do? The way successful companies keep their corporate data from becoming a data landfill is to establish, maintain a BI program and that it is led by Senior Executives (Who already have the knowledge of the organization with medium IT knowledge. So they can understand things and connect easily) and Experienced technicians to maintain a long-term BI without data landfills
So one BI tool can’t one-size-fits-all. As all users won’t need high-end analysis tool and forcing them to use the tool for simple report (that can be emailed to them on a periodic basis or access to simple online reports) is not a good idea.
It provides a comprehensive list of BI tools and other Analysis tool which can helpful to all the users for all type of requirements.
- Use of a data discovery and Visualization tool like QlikView or Tableau.
- Use of advanced analytical tools like SAS, SPSS or R.
- Enhanced operational reporting tools like Crystal Reports or Microsoft SSRS
- Special tools for tasks like budgeting and planning, consolidations,etc.
- Direct access to data via ODBC, JDBC,etc
- Access to external data such as social Media (Social Media Analytics like Sproutsocial Sysomos)
- Enterprise-class administration tools offered by SAP BI or Cognos
- Monarch, from Datawatch offers utilities to access types of data not easily accessible (Like PDF files)
- “Information Builders” has connectors for nearly every platform and application
- Rjmetrics (Can connect nearly all data and create charts combining different data, mostly used to analyze marketing data like LTV, AOV, cohorts, a monitoring tools for management)
There are hundreds of tools and technologies available to help a CIO and business users but focusing on specific requirements by understand the organization and the users is the main important thing to consider.
I will be writing more about the important tools (tableau ) specifically and how I used this tools to achieve my Company Target very soon on the next article.
Share your thoughts on recommended tools and how your favorite BI is helpful to achieve your goals on Comment section?