Data Analytics Services for Small and Midsize Businesses

Question, definition, analysis, habit

  • 9Years in business
  • 120+Clients served
  • 300+Projects delivered
  • 200+Team members
Data Analytics Services: colleagues looking at graphs

What data analytics services include

Aranv offers data analytics services that turn your company’s records into answers managers act on: we agree the questions and definitions first, clean and join your sources, build the analysis, report it where people already look, and hand over so your team can run it.

We start with definitions and evidence, not tools. Most of the work is agreeing what a word means, matching records that spell one customer three ways, and deciding which source wins when two disagree.

When the same extracts must run on a schedule across several systems, the next step is data engineering. When many people need the same numbers as a managed program, it is business intelligence. When your reports belong in one Microsoft tool, it is Power BI consulting.

From a question to a number people trust

Question, definition, analysis, habit

  1. 01 Write down the questions Managers name the decisions they make and the answers they lack.
  2. 02 Agree the definitions What counts as a customer, a sale or a late order gets settled.
  3. 03 Clean, join, analyze Records from your systems get matched, then the analysis answers each question.
  4. 04 Report and hand over Results appear where people already look, and your team learns to rerun them.

Need pipelines, forecasts or dashboards next? We will say which, and why.

Data analytics consulting for questions you keep asking

Someone asks which customers stopped ordering. The answer takes a week, arrives with caveats, and sales and finance still disagree.

  • A list of quiet customers: man in white shirt sitting in front of computer with multiple screens while holding a tablet

    A list of quiet customers

    Accounts that stopped ordering, with last order date and usual spend, so your sales manager knows who to call on Monday.

  • Margin by job and customer: a delivery man handing packages

    Margin by job and customer

    Profit after freight, returns and labor for each job or customer, showing which work pays and which only looks busy.

  • Where late orders get stuck: man in bubble jacket holding tablet computer

    Where late orders get stuck

    Order dates joined with warehouse and carrier records, showing which step or supplier holds things up.

  • Plain-English data questions: men looking at graphs on a whiteboard

    Plain-English data questions

    A manager types a question and AI writes the query over your agreed definitions. It can misread, so important answers get a human check.

Analytics for small business, without a data team: man analyzing digital stock market data

Analytics for small business, without a data team

You do not need a warehouse or a data scientist to start. Useful answers often sit in your accounting package, CRM and a few spreadsheets. We work with what you have and leave a method a finance or operations person can run each month.

What we do

  • Ranked list of questions
  • One-page definitions glossary
  • Matched customer and order records
  • Monthly routine with a named owner

What comes after the first answers

You get a plain recommendation on what to do next, including doing nothing. Some firms need only the monthly routine. Others have outgrown manual exports, need one reporting tool or want to plan ahead.

What we do

  • Slow exports: data engineering
  • Many report readers: business intelligence
  • Microsoft shop: Power BI consulting
  • Planning ahead: predictive analytics
  • Live numbers on screen: dashboard development
What comes after the first answers: persons holding printer papers with graphs
How we approach a project: business meeting with analytics display

How we approach a project

When the question moves from what happened to what will happen, you want predictive analytics. When a team needs numbers on a screen through the day, you want dashboard development. Each works better once the definitions exist.

Bring two or three questions you wish you could answer. A 30-minute conversation is the first step, and the contact page is where you schedule it.

How we work

  • Questions first, tools second
  • One written definition per number
  • Your team can rerun the work
Get started
How a data analytics engagement runs: a person holding a pencil

How a data analytics engagement runs

  • Step 1: Question session with managers

    Question session with managers

    We sit with the owner and department heads and rank the questions worth answering first.

  • Step 2: Definitions and source check

    Definitions and source check

    Each term gets a one-line definition and a source. Access is agreed before any file moves.

  • Step 3: First answers, presented live

    First answers, presented live

    We walk the people who asked through the results and explain what the data cannot say.

  • Step 4: Handover to a named person

    Handover to a named person

    The method and files go to someone on your team, who runs the next cycle.

Why Aranv for data analytics

We start from your decisions

Work begins with what a manager would do differently given an answer, so budget skips numbers nobody uses.

Definitions you keep

The written meanings of customer, sale and late order stay with you, and outlast any tool or report.

We say what data cannot answer

If your records cannot support a question, you hear that early, with what to start capturing for later.

Answers go where people look

Results land in the monthly pack, the Monday email or the system managers already open, not a new login.

 

Planning Data Analytics Services?
Book a 30-minute conversation with the team that would build it.

Talk to a data analytics expert

Data Analytics Services FAQs

  • What does a data analytics company do for a small business?

    It turns records you already hold into answers to specific questions, such as which customers are slipping or which jobs lose money, and leaves a method your staff can rerun.

  • How is data analytics different from business intelligence?

    Analytics answers specific questions, often once or on a set cycle. Business intelligence keeps a wider set of agreed numbers flowing to many people over time. Many companies need the first before they can sustain the second.

  • How clean does our data need to be before we start?

    It does not need to be clean. Cleaning is part of the work. We sample your records early and tell you which questions they can support, and which need better data capture first.

  • Can AI answer questions about our data in plain English?

    Yes, within limits. It works best over agreed definitions and well-governed tables, showing the query it ran. It can still misread a vague question, so we test it on questions with known answers.

  • What return should we expect from data analytics?

    We cannot name a figure in advance, because the value depends on what you do with the answers. We ask each manager which decision an answer would change, which tells you if the work is worth doing.

Aranv

Let’s talk about your next step

Contact Aranv to discuss your workflow, current tools, and goals. Meet with our team or send an inquiry.

Aranv at a glance

  • 9Years in business
  • 120+Clients served
  • 300+Projects delivered
  • 200+Team members

What happens next

  1. Pick a time, or send your project details.
  2. We review your goals, current tools and timeline.
  3. You get a clear next step: a scope, plan or estimate.
(347) 460-9278
sales@aranv.com

Cary, NC · Canton, MI

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