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5 Challenges Faced On Small Data Reporting
Five challenges faced on Small Data reporting
Big data is often touted as imperative to businesses, however in recent years perhaps we have been so blinded by Big Data that we are ignoring its poorer cousin, Small Data?
Big Data simply put looks at trends, information and patterns that can be utilised to forecast as well as give an overview of how your business is tracking. Big data takes high volumes of different sets of data and displays this information in a way that management can make decisions quickly and efficiently. Usually Big Data is generally generated outside of the business to assist the business make decisions moving forward.
Small Data on the other hand allows for the business to extract transactional information from data sources that end users can make use of immediately. Its focus is on providing information to the end user, so they can take action right now. It allows users to be able to determine why things happen, analyse this in real time and then take corrective action. Small Data can be generated as a sub set of Big Data or from other non-traditional data sources. The main thing to remember here is that it helps the end user achieve a result.
Big Data and Small Data each have their place in the business aiming to make inroads into improving decision making ability and resolve problems.
Formulating a plan to extract Small Data that suits each need within the company is paramount. If you ignore Small Data over Big Data then you are robbing yourself of some analytical tools that can help your company develop and improve.
Challenges facing managers looking at developing tools that allow Small Data reporting is:
- what type of data is required?
- where will it be obtained?
- who requires it?
- what format is it required?
- how will you extract the data?
The best methodology is to look at the problem you have and work backwards from that point.
As an example let’s look at the problem statement “Average Days Debtors take to pay have increased”. If we look at our challenge we can see that want to interrogate each customer and determine what the payments days are for each invoice payment has been made against (What). We check with accounts and find that this data can be retrieved from their SAP Accounts database (Where). It has been determined that Accounts Staff and Sales Account Managers will use the data (Who), accounts to chase up overdue accounts, and sales to check credit terms prior to selling. The decision then needs to be made as to what format they want to see the data in (What). An example may be a program that can run real time analysis of the accounting data and display that to screen. Selecting the right tool to extract and display this information is paramount to ensuring that the tool gets used (How). There are many good Business Intelligence tools that will allow quick extraction, analysis and display of the results the user requires.
As they say “look after the pennies and the pounds will look after themselves”. In other words Small Data can and will affect Big Data if looked after properly.
5 Public Cloud Myths Exposed
The public cloud is a hot topic in IT today. Even though it has been around for about ten years, cloud offerings from AWS, Azure and Google cloud have made the public cloud more mainstream and easier to get onto. In some instances though companies are jumping on board without really understanding it. So in an effort to debunk some myths here are five myths to consider if you are contemplating moving to the public cloud:
1. Public Cloud is Cheaper
The AWS/Azure public cloud “pay by use” methodology was a huge game changer for companies jumping onto the pubic cloud, but there is an assumption that “pay by use” will automatically make the subscription cheaper.
It can in some instances, but it should be noted that in many cases High Availability environments will usually come out cheaper with a hosting provider rather than a public cloud option. Data out transfer costs and dedicated resource costs both come into play in a big way in a High Availability environment, and things can get very expensive, very quickly. Many companies have tried out the public cloud and have gone back to dedicated resources in a managed cloud where the investment is more reasonable and consistent.
2. Everything should go to the Public Cloud
Due to the time it can take to tailor your application to the public cloud (not all applications are really built for the cloud/virtualization, much less the public cloud), not all companies environments are sitting in the public cloud. You really need to have an in-depth discussion with your IT Provider to determine what can be in the public cloud and what should be in the public cloud.
3. Full Security/Compliance Comes with Cloud Infrastructure
Security is much better in the cloud today than it has been in years past. Even though public cloud offerings like AWS and Azure offer HIPPA or PCI compliant solutions, it does not mean that will automatically make you compliant on moving to the public cloud. The infrastructure they provide to you is compliant, but once you configure your application on top of it, it becomes a completely different story.
4. Moving to Public Cloud is Simple
Some applications can be moved to the cloud simply, however putting a full environment that has not been configured and is technical within itself is a different story. Use your IT Provider or someone with the right expertise and experience to migrate the environment as it can get complicated quickly and without a good foundation getting your application to work on top of it may end up being expensive.
5. Managing the Public Cloud is Simple
Once someone has designed, built and migrated your application to the public cloud, it should be simple to manage from there – surely? You would think so but it is not the case! You really need to have your IT Provider work on maintaining, tweaking and scaling the configurations to keep your cloud “humming” along.
The simple suggestion here is to let the experts build, migrate and manage it for you. Cutting corners in the public cloud will come back to bite you.
For more information on Cloud & IT Services click here
Implementing a Business Intelligence Solution
Considerations when Implementing a Business Intelligence solution
As the type and number of Business Intelligence solutions have grown, considerations relating to the implementation need to be taken into account.
To help you avoid potential costly mistakes, consider the eight common mistakes organisations do make when they purchase a Business Intelligence solution and make the most out of your Business Intelligence software investment
Not properly defining the business problem the BI solution will solve.
Companies will jump in the deep end and purchase software before there is a definable problem that it will resolve. In some cases organisations will purchase simply because they have found that someone else is using it, so they need to as well.
Instead step back and look at your problem statement, what is needed to be able to resolve it, and then look for a BI solution that will give you that result.
Not getting acceptance from the end users of the system
Unless users are going to see a benefit to a BI solution offered and will use it, then the solution is going to fail. Bring in all stakeholders at the beginning of the process to ensure that not only the problem exists, but that everyone agrees that the solution offered will solve the problem.
Not factoring in security
Make sure that the BI solution you plan on purchasing has the ability to ensure that sensitive data remains secure and is not available for just anyone to look at.
Don’t be sold by the “sizzle”, you are buying the “sausage”
A common sales terms is “Sell the sizzle not the sausage”. Go past the bells and whistles and really concentrate on features that will matter at the foundation of BI solutions, data collection and integration between disparate data. Missing the nuts and bolts of what a BI solution should offer could leave you out in the cold when it comes time to grab all that data to present.
Not choosing a scalable solution
You want to be sure when looking at a BI solution that it will adapt and grow with your business. If it is already slow to query your data how will this affect your business two or five years down the road? The same could be said for the size of your data. As your data grows your BI solution will need to keep up with it. If you buy small you could find yourself looking for a better solution sooner than you think!
Not factoring in the mobile workforce.
In some cases a simple KPI displayed on a smartphone is as useful as any report that could be printed to screen or paper. Being able to put information that is easily digested at your employee’s fingertips is becoming more important as the workplace becomes more diverse geographically.
Rushing implementation
If you take one thing away from this blog, take this one! Rushing implementations is sure to cause problems down the track. Have a clear idea within your organisation about how long each phase is going to take and discuss that with the BI solution partner to ensure that everyone has the same expectations. Double check throughout the buying process that any changes have not changed this expectation as typically there I some scope creep as each party adds in or offers or wants more functionality.
Breaking down the project and prioritising specific outcomes you want to achieve and communicating them is extremely important. Also consider stages within the project and whether milestones will be based on reports being delivered in set time frames.
Insufficient training and consulting
Budget in plenty of training and familiarisation sessions for users of the system. Also factor in how much consulting / programming will be required to complete each project / facet of a project. Look for online training videos to have users get the most out of the training and in some cases replace initial training. Knowing what you are “up for” early in the buying process avoids disappointment later when the true cost is found out. Remember too that although best guesses can be used to judge how long a project or sub project may take, these can blow out based on inadequate information or improper definitions of the business process.
BI solutions can identify opportunities, highlights risks and forecast trends if properly implemented. Foresight into the whole solution process, from identifying the problems the organisations have, the selection of the BI solution and the implementation of that paramount to achieving that result.
For more information on Business Intelligence or other IT Solutions contact us
Preventing Data Leakage
Are you at risk of leaking data?
We see the headlines on a regular basis, ‘…details of any Australian for sale on darknet’, ‘Personal details of world leaders accidentally revealed…’ These regular occurrences highlight a major problem facing todays businesses, a problem which only continues to grow.
It is hard to measure the cost to a business once an incident has occurred. Damage can go well beyond monetary values and often the biggest damage to a business can be one of reputation, with customer data making up 73% of leaked information (based on publicly disclosed breaches).
An IBM survey suggests that the average estimated cost is around 2.6 million dollars for a business to recover from such an event.
However, the question shouldn’t be ‘how much would it cost to fix’, the question is how do we prevent data leakage?
First let’s get an understanding of the leading causes of data leakage and the types of data involved.
The threat of data leakage can be split into two categories, Internal threats and External threats. As you would have guessed, Internal threats are made up of employees, contractors, business partners and others with insider access. External threats are usually cyber criminals, hacktivists or competitor sponsored attacks. It is necessary to identify that there is some middle ground, where someone inside the company can assist an external threat.
Although we have listed insiders as Internal threats, it is important to note that 96% of insider data leakages are caused by inadvertent actions often relating to malware, stolen devices and or failure to follow internal IT polices.
What’s the Solution?
The good news is that there are many technical solutions and products designed to mitigate these risks, both inside and outside the organisation.
It is imperative to build a sound strategy around data leakage, and below are key requirements for the most important aspect of Data Loss Prevention (DLP)
Identify / Prioritise data – Not all data is equal
Categorise data – Apply persistent classification tags to the data that allows tracking throughout the organisation
Monitor data movement – Identify what processes put data at risk
Communication and Policy – Develop polices surrounding DLP and acceptable use of company resources
Employee Education – Employees often don’t realise that their actions can result in data leakage. A strong employee educational focus in conjunction with policies and procedures can reduce the insider data leakage risks in an organisation by up to 80%
For more information on Data Leakage or other IT Solutions contact us
