Data governance (DG) alludes to the general administration of the availability, ease of use, integrity, and security of the data utilized in an organisation. A sound data management program incorporates a governing body or committee, defined procedures, and its execution

Since its presentation in 2004, the DGF Data Governance Framework has been utilized by many organisations around the world. It centered at the mid-level supervisors who must meet up to settle on cross-practical choices, set strategies, and execute on it. It unites cross-utilitarian groups. The Data Governance Institute (DGI) gives top to bottom, merchant unbiased Data Governance best practices and direction.



data-governance.jpg 3



In-road To Adequate Data Governance

1 Governing body: The initial step in any effective data governance project is recognizing a person in the organisation who possess the designated power and skills, then assigning the individual to get things going. There is no alternatives to strong administration.


Step 2: Survey your circumstance

When you have the initiative group set up, it needs to study the region and stock current practices crosswise over numerous different areas. The groups need to see over the stove-pipes, and an endeavour data government strategy is basic for this assignment. It helps benchmark where the organisation data programme is today and conveys a guide to figure out where it will be tomorrow.

Step 3: Develop an information administration procedure

After the data government evaluation, the administration chamber ought to investigate making a dream of where it needs the organization’s information administration practices to be in the following couple of years, in this way making a dream for what’s to come. The gathering ought to work in reverse, and make practical turning points and venture arrangements to fill pertinent holes by building up key execution markers to track advance and convey yearly reports.


Step 4: Calculate the likelihood of danger

Knowing how data has being mishandled in the the past is a pointer of how it may be traded off and uncovered later on. Each association has reasons, occasions and misfortunes that are lost in stovepipes, progressive systems and business reports. This information is as of now accessible and unused by most associations. Gathering it, relating its importance and considering misfortune patterns after some time can help any association change hazard administration into an actuality based, business insight strategy for breaking down past occasions, determining future misfortunes and changing current approach prerequisites to enhance your relief procedures.

Step 5: Calculate the estimation of your Data

If an organizations don’t recognize what it’s worth, they can’t improve, ensure or measure the estimation of the information to the primary concern. Information isn’t a typical thing. It’s similar to water out of a tap—crucial to life yet so frequently underestimated. In any case, you can’t ascertain the benefit of something if you don’t have the foggiest idea about its price.

6 Monitor the efficacy of Your control

Data governance is to a great extent about hierarchical conduct. Associations change consistently, and along these lines their information, its worth and hazard likewise move quickly. Shockingly, most associations evaluate themselves just once every year. If a business is unable to weekly adjust itself   to suit the current societal demand, then it’s isn’t governing any change.

In conclusion, assurance and evidence that data is managed effectively reduces regulatory compliance risk and duplication. It enhances trust in operational and administration. knowing individual their responsibilities and escalation routes reduces the time to resolve data issues, increase capacities to respond to change and events faster through understanding across the users

Safeguarding corporate information and using improved data quality will help companies not only keep auditors and regulators satisfied, but also retain customers and drive new business opportunities.















































































































































































































































































































































































































Comments on ‘R’ Graphic project

The r graphics project was a bit difficult to understand but my class notes and lecture’s examples assisted my interest. Initially I had difficulty understanding the graphics user interface for the R program. I eventually decided on a simple data as I need to explore some more on R later.

How Achieved

Data is only useful when we can effectively communicate it to someone else, and to do that, we need to format it into some sort of meaningful visual representation. First I had to play around with the R program by typing simple examples from ‘try R’ lecture. Next, I struggled to understand what data frame was and how to arrange this in R. To make graphs with ggplot2, the data must be in a data frame, and in “long” (as opposed to wide) format. I had to look up some YouTube videos to understand how to generate my required graph from my data frame and this took some time.

With bar graphs, there are two different things that the heights of bars commonly represent. I understood from reading that I have to do this with stat-bin. This is used specifically in ggplot2 to calculate the number of cases. My data frame was loaded after a few trials. The count, in my case, x=time and value y=total bill are used by ggplot2 to represent the bar length and height respectively. I used the example from one of the packages named reshape2.

The height of my bar chart represent the value in a column of the data frame by using stat=”identity”. I found that I can tweak my values as necessary and this would generate different graphs. The graph outcome from my data frame is as below.

Information Gleaned

This is a simple data showing lunch and dinner in a restaurant and the total bill paid for the meals. As explained the y axis, which is the value is represented by total bill and the x axis which is the count is represented by time. As can be seen from the graph, the height for the lunch and dinner differs, with lunch costing almost £15 and dinner almost £20. The graph affords the privilege to visualise at an instance sales in a restaurant and can be used effectively to determine trend of sales, profit and loss, customers satisfaction of type of meals served and even trend of days in which the restaurant has highest number of visitors.

The Code Used

Very basic bar graph

ggplot(data=dat, aes(x=time, y=total_bill)) +
# Map the time of day to different fill colors
ggplot(data=dat, aes(x=time, y=total_bill, fill=time)) +

## This would have the same result as above
# ggplot(data=dat, aes(x=time, y=total_bill)) +
# geom_bar(aes(fill=time), stat=”identity”)
# Add a black outline
ggplot(data=dat, aes(x=time, y=total_bill, fill=time)) +
geom_bar(colour=”black”, stat=”identity”)
# No legend, since the information is redundant
ggplot(data=dat, aes(x=time, y=total_bill, fill=time)) +
geom_bar(colour=”black”, stat=”identity”) +


r-graphics assignment








Other Ideas/Concept that can be represented

One of the main reasons data analysts turn to R is for its strong graphic capabilities. One could create basic graph types. These include density plots e.g. (histograms and kernel density plots dot plots, bar charts (simple, stacked, grouped), time and pie charts (simple, annotated, 3D), box plots (simple, notched, violin plots, bag plots) and scatter plots (simple, with fit lines, scatter plot matrices, high density plots, and 3D plots).We can also customize and annotate graphs.


 The image below is my class work 

R details




R graph coloured


Conclusively, I will like to confess that the course content is richer and challenging than I expected,  but with determination, persistence, lecture notes and a patient tutor, I am able to sail through.





So, what is considered big data?

Big Data is an advancing term that depicts any voluminous measure of structured, semi-structured and unstructured information that can possibly be dug for data.big data can be portrayed by 3Vs: the great volume of information, the wide mixed bag of sorts of information and the speed at which the information must be prepared. Albeit big data doesn’t refer to any particular amount, the term is frequently utilized when talking about petabytes and exabytes of information, quite a bit of which can’t be incorporated effectively.



Value: the capacity to give reasonable worth from initially undiscovered information

Volume: Larger measures of information than ever perceived

Variety: Ability to break down and unite information of distinctive configurations, sources and sorts.

Variability: Ability to work with capricious burdens, configuration, volumes and styles

Velocity: Performing examination on the fly, before putting away the information.












Big data analytic is often associated with cloud computing because the analysis of  large data set in real-time requires a platform like Hadoop to store large data sets across a distributed cluster and Map-reduce to coordinate, combine and process data from multiple sources

Big Data finally permits analytics that before were too hard, excessively extravagant or too time intensive. Volume is not by any means the only obstacle: velocity, variety and variability could likewise be reasons why this investigation is troublesome. Big Data makes breaking down “troublesome” information conceivable.

big data advances have come to the level of development important to make staggering computational accomplishments moderate. Also, this computational capacity is currently unmistakable to the overall population. Facebook,, and seek motors, for example, Bing, Yahoo!, and Google are prime cases.

The ability to leverage new technology and approaches, which enable us to affordably handle more data and take advantage of the variety of data that lives outside of the typical transactional world—such as unstructured data.













Data are generated steadily in day-to-day activities, and the degree to which those data enable others to shape how our world responds to us based on our own actions.

Facebook posts are information focuses. Web quests are information focuses. Google has to be acclaimed for the expansion of the information focuses it catches on its clients and the span for which it holds such information. Buys made on Amazon can be returned to years after they happen, as can things saved money on the client’s “list of things to get.” Retailers spare items bought while utilizing a club card as information focuses.

Google has made gathering and examination one stride further. In learning about your every day life through those exercises intervened by your telephone and PC, it tries to anticipate what you will do next and serve applicable data. Google Now is an individual associate application Google took off in mid-2012, utilizing hunt and other history to present helpful data without client request.

Microsoft is doing similar things with its latest windows 10 design. It is my conclusion that in the years ahead big data will surpass anything we can imagine more so as we see companies re positioning themselves  to expand in this area.



 Big Data Now, 2 nd Edition, O’Reilly Media. (2012)  Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Businesses, Minelli et al (2013), Wiley & Co,  Business intelligence and analytics: from big data to big impact, Chen et al (2012), MIS Quarterly Vol. 36 No. 4, pp. 1165-1188/December 2012









What is data protection?

Data protection is the process of safeguarding important information from corruption and/or loss. It is your fundamental right to privacy. The data controller must comply with data protection principles. You can access and correct data about yourself.

Data protection’s commissioner’s office was established in 1988 and became fully active in 19th April 1989. .   It was amended in 2003 by data protection amended act. The current commissioner is Helen Dixon. She is to ensure that individual’s rights are secured as set out by the acts.

Their main objective is to protect the individual’s right to privacy by enlightened people to know, and to exercise control over the use of their personal information, according to the Data Protection Acts, 1988 & 2001

It is the duty of an organisation or individual (Data controllers) to keep people’s information and details safe. This is information which identify with a living person who can be distinguished from those information, or and other data which is in the ownership of, or is liable to come into the ownership of, the information controller.

It is an offence under regulation 13(13) of S.I. 336 of 2011, for the sender of an e-mail or SMS for direct marketing purposes to disguise or conceal the identity of the sender or to fail to provide a valid address to which the recipient can send a request that such communication shall cease.

Information Controllers are liable to 8 commitments.

They are committed to guarantee that information is:

  • Kept safe and secure
  • Kept exact
  • Adequate and pertinent
  • Retained for no more than expected
  • Not revealed to outsiders unless it’s mandatory.
  • Obtained and handled reasonably
  • Kept just for one or more determined legal purposes







Data Subjects……..Know Your Rights

Are you aware of your right to guard and follow up your details?

The privilege of access to all the information

The privilege to have information revised or updated.

The privilege to have information deleted, if there is not a real explanation behind holding it, or if it is obsolete.

The privilege to look for pay for harm or pain brought on by off base information or inappropriate

Under Section 3 of the Data Protection Actions

You have the right to data protection when your details are:

  • held on a computer;
  • held on paper or other manual form as part of a filing system;
  • made up of photographs or video recordings of your image or recordings of your voice

It is very deplorable to know about some renown organization who were guilty of information assurance infringement. The consent to compel Internet organizations, for example, Google (GOOGL.O) and Facebook (FB.O) to submit to extensive standards is an initial phase in a more extensive change bundle to fix protection laws – an issue that has picked up noticeable quality after disclosures of U.S. spying in Europe.


vodahone 4



google and Facebook

Vodafone’s (VOD.L) recent  revelation of the degree of phone call reconnaissance in European nations demonstrated the practice is not constrained to the United States. The world’s second-biggest cellular telephone organization, Vodafone is headquartered in the United Kingdom.

Nevertheless, data protection is so crucial that if an individual, firm or organisation is big enough to break the law, they should be made to face the wrath of the law since no one is above the law.







With the coming of the internet, business processes have undergone massive change. Information technology has made outcomes, forming ways into all walks of life, for example, in offices, buying things at supermarkets, using rails, airport, hospitals, transport, hotels as well as education and banking. It is being used for decision making in a wide range of ways.








Web-enabled enterprises and global e-business and e-commerce systems are becoming commonplace in the operations and management of today’s business enterprises. Information systems is now solidly entrenched as a strategic resource in the modern organization.

Despite the fact that we have extended our capacities with respect to utilizing data frameworks for directing business, today’s data frameworks are as yet doing likewise fundamental things that they started accomplishing over 50 years prior. Regardless we have to process exchanges, keep records, furnish administration valuable and enlightening reports, and backing the foundational bookkeeping frameworks and procedures of the association. What has changed, in any case, is that we now appreciate a much more elevated amount of joining of framework capacities crosswise over applications, more noteworthy network crosswise over both comparable and unique framework segments, and the capacity to reallocate discriminating figuring undertakings, for example, information stockpiling, preparing, and presentation to exploit business and key opportunities

Development Processes. Although there are a seemingly endless number of software applications, there are three fundamental reasons for all business applications of information technology.


They are found in the three vital roles that information systems can perform for a Business enterprise:

  • Support of business processes and operations.
  • Support of decision making by employees and managers.
  • Support of strategies for competitive advantage.





Data frameworks intended to bolster business procedures and operations might likewise be making prepared learning for PCs to meet up on business choice thereby improving rivalry possibilities. The same is valid for the other 2 parts above. Today organizations are continually making an endeavour to finish and complete things on their frameworks to let data move freely through them, which makes an expansion considerably more prominent and ready to make prepared modification and business support than any of the individual framework parts could give.

Support of Business processes and operations

As a user, we regularly deal information systems that support business processes and operations, for example when we transact business in general stores. Most stores now use machine based information system to help their employees record buying goods from the store for money, paying workers, making inventories, as well as value sales trends. Stores operations will grind to a halt without the support of such information systems. Support of Business decision through information systems also help store managers and other business experts make better decisions. For example, decisions about what lines of goods need to be added or ended, and what amount should be put into business that they have need of are representatively made after observations.

Personally I believe as technology advances, better decisions have to be made to optimise the use of information systems.


Management information system; Kenneth C Laudon, 12th edition


Creating a Heatmap with Fusion Table



The project entails creating a fusion table outlining an Irish Population heatmap based on the 2011 census data. The map is to show random distribution of counties in Ireland based on population density.


  1. Importing Data

Raw Data used for the project was downloaded through the following links

Irish Population Census 2011 from CSO website:




  1. Irish KMZ Datafile from independent website:





  1. Preparing files for analysis


To import the data into Fusion table for analysis, the raw data from CSO was sorted as follows:

  1. The population data was copied to google spreadsheet and filtered. The original data contain 4 columns, namely province, males, females, total persons. This was filtered and cleaned to remain two columns namely province and total persons. Secondly the raw data from the CSO contained North and South Tipperary population figures .These were combined into one value for Tipperary, and Dublin total value was used instead of areas under Dublin.


The cleaned data and the kml file were imported into fusion table via google drive.

A new google spreadsheet was generated using information from (a) above and obtaining the area of each county (Sq. Km).The areas of each county in Square kilometres was obtained from the website below through google search:





The new google spreadsheet generated contained province, areas (sq. km) and population density which was computed for each of the 26 counties by dividing the total number of persons from (a) by the areas per square km. The spreadsheet obtained is as below containing 3 columns: province, areas and density calculated (see sample below).

Province, County Areas (Sq. km) Pop. Density
Carlow 894.09 61
Dublin 917.46 1388
Kildare 1686.69 125
Kilkenny 2059.47 46
Longford 1037.3 38
Louth 817.92 150
Meath 2329.34 79
Offaly 1990.26 39
Westmeath 1751.7 49
Wexford 2343.18 62
Wicklow 2013.65 68
Clare 3149.44 37
Cork 7435.56 70
Kerry 4682.18 31
Limerick 2677.98 72
Tipperary 4248.93 73
Waterford 1831.62 62



3 Converting data to Map

Fusion Tables allows you to present your data in a visual, interactive way. These data were collated after importing into fusion table and merged to obtain the population and population density heatmaps as required.

The spreadsheets for population and population density loaded into Fusion tables, separately, along with the kml data generated two maps. The data sets were divided into bin sizes each and a colour assigned to each as shown below.




Population Density Map


The maps were filtered and colours assigned to boundary. The geometry for Carlow was left out so as to visualise how the distribution would look. From the map, Dublin has the highest density and Leitrim the lowest. The overall average density is in the region of 105 Sq. Km






Other ideas and concepts that could be represented include representing the population using marker icons after geocoding as show below.









                   decision Supportbusiness-intelligence-basics-buzzwords


Business Intelligence (BI) reliably rates at the highest point of organizations’ venture needs. Regardless of its need, agents routinely grumble about data over-burden from one viewpoint and the failure to get to applicable information on the other. As an innovation, BI utilization stays unassuming, with noteworthy undiscovered potential.

Business Intelligence is a collective information – about your customers, your competitors, your business partners, your competitive environment and your own internal operations that gives you the ability to make effective, important and often strategic business decisions. Its a

Technology that Allows:
•Gathering, storing, accessing & analysing data to help business users make better decisions

Set of Applications that Allow:
•Decision support systems
•Query and reporting
•on-line analytical processing (OLAP)
•Statistical analysis, forecasting, and data mining
Help in analysing business performance through data-driven insight:
•Understand the past & predict the future






Business intelligence cuts across all functions and all industries. BI touches everyone in a company and beyond to customers and suppliers. Business intelligence can only provide business value when it is used effectively by people. There is a correlation between the effective use of business intelligence and company performance

− Enable critical data and analysis tools as identified for multiple business groups
− Provide data integrity, simplification and standardization for the business areas
− Provide dynamic and interactive reporting
− Reports create simplicity and reduce Business Technology dependence for report creation and updates

− Cost savings by reducing the business users effort to create these reports and validate the data
− Rapid access to data from all sources
− Standard KPI and dashboard reports
− Allow for data mining and predictive analytics

At the point when any specific metric is not where it ought to be, business knowledge permits clients to investigate the basic subtle elements to focus why measurements are off target and to make a move to enhance the circumstance. In the past, if administrators checked the business through paper-based reports, they had no adaptability to investigate why the business was working a certain way. For instance, numerous organizations use BI to screen costs to guarantee expenses do not surpass spending plans. As opposed to holding up until the end of the quarter to find that unreasonable costs have lessened benefit, opportune access to cost information permits chiefs first to distinguish which special unit is over financial plan and after that to make quick moves to decrease extra time pay or travel costs, or to concede buys.

Business Intelligence Layers
Every BI deployment has an underlying architecture. The BI architecture is much like the engine of a car—a necessary component.







Source system layer is from where the information is drawing near the framework for investigation. Wellspring of information can be any CRM system, money, HR, deals, promoting and so on.

Warehouse layer is the place all the information assembled from distinctive sources are coordinated in type of information stockroom.

Reporting layer is something where in view of information investigation and reporting is done which help in taking the business choice.




Utilized viably, business knowledge permits associations to move toward execution. Business execution is measured by various money related markers, for example, income, edge, gainfulness, expense to serve, and so on. In advertising, execution additions may be accomplished by moving forward reaction rates for specific battles by recognizing qualities of more responsive clients. Taking out incapable crusades spares organizations a huge number of dollars every year.






Review Article; An Overview of Business Intelligence

By Shurajit Chaudhuri, Umenshwai Dawal, and Vivek Narashayya

 Big Data Now, 2 nd Edition, O’Reilly Media. (2012)  Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Businesses, Minelli et al (2013), Wiley & Co,  Business intelligence and analytics: from big data to big impact, Chen et al (2012), MIS Quarterly Vol. 36 No. 4, pp. 1165-1188/December 2012