Priti's guess: Every night at 2 a.m. Priti decides how many of each loaf the Mill Lane bakehouse will bake for the four shops.
What happened
- For a year she baked 1,450 loaves every night, whatever the day.
- On Mondays about 130 were left over.
- On Saturdays the rye was gone by eleven.
The answer was already sitting in the bakery's computers. Nobody had asked them.
Every sale leaves a record. The till in each shop notes what was sold, where, when and for how much. The bakery's app (4.5.4) adds who bought it. All of it is kept in one organized store of records that can be searched, sorted and updated (a database). In a business, a database is usually about customers or sales.
| Date | Time | Shop | Item | Price | App member |
|---|---|---|---|---|---|
| Sat 9 Jan | 08:12 | Market Square | Rye loaf | $3.00 | No |
| Sat 9 Jan | 08:13 | Station Road | Coffee and croissant | $3.00 | Member 0417 |
| Mon 11 Jan | 07:02 | High Street | White loaf | $3.00 | Member 0088 |
What makes it a database (its features)
Large amounts, easy to find
It stores, organizes and retrieves thousands of sales, so Lena can pull every Saturday rye sale in seconds.
Each fact stored once
A member's details are kept in one place and linked to each sale, which cuts out repetition and the errors that come with copying.
Several users at once
Aisha, Kofi, Jonas and Priti can all look at the same, up-to-date records at the same time.
Secure
A password controls who can get in, and each person sees only what their job needs.
Holding the data is only the start. Working with it to answer a business question, using averages, charts and the search for patterns, is data analytics. Lena's question was simple: how many of each loaf should Mill Lane bake on each night of the week? Two years of till records gave the average sales of every loaf for every weekday, and a forecast for each night.
What the answer was worth: Priti now bakes to the forecast, between 1,200 and 1,450 loaves a night. The unsold loaves have fallen from about 130 a night to about 70, and the rye lasts until closing on Saturday.
Sixty fewer loaves thrown away, at about $0.90 of ingredients each, is $54 a night: close to $20,000 a year.
When the tills, the app, the ovens and the staff rota feed one system that gives managers the information they need to decide, the business has a management information system. Priti's forecast is the smallest version of one: data in, a better decision out.
Free preview
This is the free notes preview
You're reading the free notes. Aimnova Pro unlocks the full study experience — and you can try it with your first topic free to keep:
- FlashcardsLock in vocabulary and key terms with spaced repetition.
- Practice questionsAnswer exam-style questions and get instant AI marking.
- Mock exams & past-paper vaultSit full mocks and see exactly how examiners award marks.
- Personalised study planA daily plan built around your exam date and weak areas.
An email from Valley Grain: On a Tuesday morning Kofi, who runs the Market Square shop, opens an email from Valley Grain.
What the email says
- It has the cooperative's logo and the usual greeting.
- Their bank has changed, it says: please pay this week's flour invoice, $4,200, into the new account below.
- The sender's address is one letter different from Valley Grain's.
A deliberate attack on a business's networks, computers or other devices is cybercrime. Defending them against attack is cybersecurity.
Kofi rings Valley Grain on the number in the bakery's own records. Nobody there sent the email. The $4,200 would have gone straight to a criminal.
Common attacks
- A fake email or message that tricks staff into paying or giving a password (phishing)
- Software that locks the database until a ransom is paid (ransomware)
- Theft of customers' details, such as the app members' emails and phone numbers
- Breaking into the tills or the website to take payments
What an attack costs
- Money paid to the wrong account, or a ransom
- Days without tills, forecasts or orders
- Customers' trust, once their details are stolen
- Fines, because the law requires businesses to protect personal data
Cybersecurity at Lena's
- Strong passwords and a second code sent to a phone before anyone can log in
- Training staff to spot fake emails, and a rule to check any change of bank details by phone
- Copies of the database kept somewhere separate (backups)
- Software kept up to date, so known weaknesses are closed
The weak point is usually a person: No firewall would have stopped Kofi paying the invoice. The email was aimed at him, not at the computer.
That is why the cheapest defence is often the best one: staff who know what an attack looks like, and a rule that nobody changes a supplier's bank details on the strength of an email.
The more Lena relies on her data, the more an attack can stop. If ransomware locks the database, Priti is back to guessing at 2 a.m. If the app is broken into, 900 members' details are in a criminal's hands. Cybersecurity is part of the cost of every system in this micro.
Know your predicted grade
Take timed mock exams and get detailed feedback on every answer. See exactly where you're losing marks.
Lena's database used to sit on one computer in the back office of the High Street shop. Now it lives in the cloud.
Before: one office computer
- When that computer was switched off, nobody else could see the figures.
- One burst pipe could have destroyed them.
Now: the cloud, for $90 a month
- Priti checks the forecast on her phone at 2 a.m.
- Jonas checks it at Park Road at 7.
The systems everything else depends on: Some systems are so basic to how a business and a country work that everything else stops without them (critical infrastructure). For information systems, three matter most: data centres, cloud computing and artificial neural networks.
Critical infrastructure, at Lena's
Data centre
A building full of computers (servers) that store and process data for many businesses, with backup power and cooling. Lena's records now sit in one, run by her cloud provider.
Cloud computing
Renting storage and software over the internet from a provider's data centre instead of owning the computers. Lena pays $90 a month, can use it from any shop, and the provider keeps the backups.
Artificial neural network
Software built loosely like the brain, as layers of connected points that learn patterns from examples. The forecast is one: it learned from two years of sales and weather which nights sell the most rye.
Three more technologies run on that infrastructure. A computer doing tasks that normally need human intelligence, such as forecasting, understanding speech or planning a route, is artificial intelligence (AI). Devices that send data to each other with no person involved form the internet of things (IoT). A computer-made 3D world that a person can step into and practise in is virtual reality (VR).
| Technology | At Lena's Bakery | A benefit | A risk |
|---|---|---|---|
| Artificial intelligence | The forecast; a chatbot that takes the cafés' cracker orders at night | Better guesses than a person can make, at any hour | Wrong when something new happens that it has never seen |
| Internet of things | Sensors in the ovens and the cold room send readings to Marco's phone | An alert at 3 a.m. if the cold room warms, before the dough spoils | Every connected device is another way in for an attacker |
| Virtual reality | The oven maker's headset course on the planned $45,000 deck oven | New bakers practise before the oven arrives, with no dough wasted | Headsets and courses cost money, and a real night shift is not a simulation |
It all hangs on the connection: If the internet at Mill Lane goes down, the forecast is out of reach. If the cloud provider has a fault, four shops lose their records at once.
The benefit of relying on shared infrastructure is that someone else runs it. The risk is that someone else runs it.
Half a million sales a day: Goldcrust plc has 400 bakeries and sales of $451 million a year: about half a million sales a day.
What Goldcrust records
- Each sale
- What its app members buy
- Where they are
- The weather
- What people post about Goldcrust online
- Readings from the machines in its Seren factory
No spreadsheet could hold it. That is the point.
Data sets so large, arriving so fast and in so many forms that ordinary tools cannot handle them are big data. Lena's database, a few thousand sales a week, is ordinary data that she analyses. Goldcrust's is big data: numbers, locations, photos and comments, pouring in every second from 400 places.
What Goldcrust finds when it digs (data mining)
Weather and what sells
Pies and soup sell 40% more on wet mornings. The Seren factory now bakes to the rain forecast, not to last week's sales.
What is bought together
Customers who buy a coffee before 8 a.m. usually add a pastry. A coffee-and-pastry deal is built around it.
Who is drifting away
App members who miss two weeks rarely come back. The app now sends an offer on day ten, before the habit breaks.
Where to open next
Streets where app members already walk past, but no Goldcrust bakery stands, go to the top of the list.
Searching large data sets for patterns, trends and links, and using them to predict what will happen, is data mining. It turns big data into decisions: what to bake, which offer to send, where to open.
What data mining gives Goldcrust
- Decisions based on evidence. Bake to the rain forecast, not to a manager's hunch.
- Less waste. Fewer pies baked for dry mornings and thrown away.
- Offers people want. A deal on what customers already buy together.
- Customers kept. The day-ten offer reaches them before they are gone.
Where it can mislead
- A link is not a cause. Sales and rain moving together does not prove one causes the other.
- The past is not the future. A new rival or a strike breaks every pattern.
- Only who it can see. Customers who pay cash and have no app are missing from the data.
- Privacy. Customers may not know how much their app is telling Goldcrust.
Three words, three jobs: Big data is the raw material. Data mining is the digging for patterns in it. Data analytics is the whole job of turning data into answers.
The decision is still a manager's, and so is the responsibility for it.
Get feedback like a real examiner
Submit your answers and get instant feedback — what you did well, what's missing, and exactly what to write to score full marks.
In 4.5.4 Lena launched a loyalty app: a stamp for every loaf or coffee, the tenth one free.
By the end of November 250 Station Road commuters had it. There it was a way to promote the bakery and keep customers coming back.
A free loaf for a year of data: Every stamp is also a record: who bought what, when, and in which shop. By January the app has 900 members, and each of them is telling Lena exactly how they shop.
A customer loyalty programme rewards customers for buying again and again. Seen from inside a management information system, it is also one of the best sources of data a business has.
| What the app data shows | The decision it supports |
|---|---|
| 40 of the 250 Station Road members have not been in for two weeks since Crumbline's kiosk opened | Send those 40 a free coffee to win them back, instead of cutting prices for everyone |
| Members at Market Square buy rye mostly on Fridays and Saturdays | Bake more rye for those two nights only |
| Few High Street customers use the app at all | Keep the paper stamp card there, or those customers miss out |
What it gives the business
- Data for decisions about baking, offers and shops
- Offers aimed at the right members, not discounts for all
- Regulars kept when a rival opens nearby
What it costs
- The rewards: a free loaf is $3 to the customer but about $0.90 of ingredients to Lena
- The app itself, and the time to read the data
- Members' details that must be kept safe from cybercrime
The ethical questions
- Do members know how much their stamps reveal, and did they really agree?
- Customers without a smartphone never get the offers: unfairness built into the system
- Would it be right to sell the members' data to anyone else?
Weigh it, do not list it: A loyalty programme is worth running if the extra visits and the better decisions are worth more than the rewards, the app and the risk to members' data.
At Lena's: for
- The reward is cheap, since a free loaf costs her about $0.90.
- The data has already won back commuters from Crumbline.
At Lena's: against
- The weakness is who is left out: the older High Street regulars.
Ready to ace Management information systems?
You've seen the preview. Here's what you'll unlock:
Bite-Sized Study Notes
Full syllabus broken into chunks that stick
Exam Practice
See exactly how to score full marks
AI Feedback
Know exactly what examiners want
Smart Study Plan
Know exactly what to study next