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Everything You Need To Know About Automated Analytics

Everything You Need To Know About Automated Analytics

Chelsea Wise

The Expert's Guide To Getting It Right.

Ask 100 people to analyse a spreadsheet filled with rows and columns of data. You’ll get 100 different answers. Even if the business problem is clear. Even if the data is clean, complete and labelled.

Although data analysis often creates havoc — multiple versions of the ‘truth’, spreadsheet silos, analysis paralysis, and significant errors such as those made by respected and influential Harvard economists — in the world of data analysis, analytics, visualisation and business intelligence (BI), what matters is:

  1. … the new machine age makes automated data analysis and insight discovery now possible. So whether you think AI is about robots or a specific machine learning algorithm, in the category of enterprise BI, there is now an opportunity to analyse data, audit and govern analysis, communicate insights and reach more people than ever before.
  2. … instead of one spreadsheet creating havoc, the newfound ability to analyse data and communicate insights at scale, means less time spent manually trolling through spreadsheets, pivot tables and checking formulas. And more time making sense of insights, getting answers to business questions, and finally being able to collaborate with colleagues in a data-led way about growth opportunities. Not stuck in spreadsheets. Or hamstrung by a lack of data literacy.

But how does Automated Analytics actually work?

  • What is Automated Analytics? Self-Service Business Intelligence?
  • How is it different to traditional BI tools like Power BI and Tableau? How do you know when to use the right tool for the job to not confuse employees?
  • How do you know whether it’s right for you? How do you find the right use-case to optimise the data you have, instead of waiting for data nirvana? How do you show value in the midst of a multi-year data transformation?
  • What does implementation look like? How do you implement a proper BI process to optimise decision making every quarter? How does it fit with your tech stack? How can you restructure your data and analytics team?
  • What does success look like? How can you align this to proper revenue growth? What is the ROI of automated data discovery?

To address this gap, Hyper Anna has created ‘The Anatomy of Automated Analytics’ — a 100 page guide outlining the process to automate business intelligence that’s created millions of dollars of growth across finance, procurement, sales, marketing and operations teams.

Ultimate Guide To Automated Analytics (2021)

Designed for executives, we’ve interviewed seasoned CEOs, CFOs and CDOs to help you learn what it’s really like in to transform your business intelligence function. We’ve also combed through the most important HBR, MIT, McKinsey and Big 4 research to help you understand the future of data teams, how technology will reshape organisations & where Automated Analytics can supercharge work.

In today’s article, we share key takeaways from The Guide:

  1. What is Automated Analytics?
  2. Automated Analytics: How It Works
  3. Automated Analytics: 10 Things To Look For
  4. Automated Analytics: The Value It Brings (Real Stories)
  5. Best Automated Analytics Tools 2021
  6. For The Skeptics: Why Do I Need Automated Analytics, I’ve Already Got Tableau, Power BI?
  7. Conclusion

PART 1. What Is Automated Analytics?

Also known as: Self-Service Business Intelligence.

Self-Service Analytics is a form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support. Self-service analytics is often characterised by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access. Gartner (2021)

Who is it for?

Designed for best-in-class companies that can’t wait until their five-year digital transformations are complete before thinking about streamlining data consumption. Instead, they make their business-intelligence capabilities available to employees on a self-serve basis from the start. Only then will they be placed to accelerate solutions that will fuel growth.

What will you get?

You need a way to uncover actual business insights, understanding drivers of your business and easily look at any area within your data. You also need a turnkey solution that won’t take months to set up or train with.

  • Data Democratisation: You want to drive data adoption. But many people don’t know how to use data, and even when they do, it can be difficult to access. Self-service BI makes it possible for people across your business to access data insights, without a degree in data science.
  • Data Analyst Productivity: It’s hard to find good talent, so you want your data and analytics team to be able to do more with less. Use the power of automation and enterprise AI to help your team increase its productivity.
  • The Data Driven Enterprise: You want to use data to inform decisions throughout your company. Automating analytics, allows you to drive value and democratise data. With a roadmap in hand, your team will be sailing toward a data-driven future.
  • Solution Acceleration: Best-in-class companies don’t wait until their five-year digital transformations are complete before thinking about streamlining data consumption. Instead, they make their business-intelligence capabilities available to employees on a self-serve basis from the start. Only then will they be placed to accelerate solutions that will fuel growth.
Wait, what’s wrong with the usual way of getting data-led insights?
The Business Case For Automated Analytics
  • Excel Analysis: Offline, incredibly manually intensive, not repeatable, version control nightmares, tedious long work.
  • Dashboards: Reliant on access to the right talent. Not always comprehensive & difficult to get to to the ‘why’ — limiting decision intelligence. Not scalable or agile.
  • Analysis from analysts: Takes time due to volume of requests. Talent shortage makes answers to key questions difficult. Business suffers.

PART 2. Automated Analytics — How It Works

Hyper Anna automates business analytics and reporting, at scale.

We explain how it works in the context of Hyper Anna.

Built from the ground up, Hyper Anna’s IP covers the technical know-how across the entire journey — data ingestion to insights. Key mechanics include data profiling (how Anna makes sense of raw data), natural language processing (how data can be queried in conversational form), and after the analytical number crunching, the data story composition and presentation engines (so you know what you’re seeing and why).

Hyper Anna + Automated Analytics

PART 3. Automated Analytics: Top 10 Things To Look For

  1. Integrates with services you already use — Zero effort for anyone in your data team to connect a tool like Hyper Anna straight to your source systems.
  2. Automated data prep — Smarts to deal with data quality & prep, so you’re not waiting for an army of analysts or data nirvana to yield unprecedented business insights.
  3. Streamline data consumption. In minutes. — Automating your base layer of business reporting, elevates the role of data teams from ‘back-office’ to driving focus & value.
  4. Reduce data costs. Without jeopardising growth — Eliminates the ever-growing backlog, keeping pace with business demands, minus the cost of hiring & training talent to do it all.
  5. World-class dashboards. Minus the hassle — Deliver executive-ready intelligence at scale, never starting from scratch again. Eliminates hassle of ever-changing business requests or building dashboards that don’t get used.
  6. Analytical excellence — Automates routine business analytics leaving no angle of your data unturned, time saved to focus on bespoke data science & modelling.
  7. As granular as it gets — The only BI solution that creates executive-ready dashboards & bespoke data stories automatically. Drill down to anything you like.
  8. Analytical excellence. Minus the lingo — Uncover truths you didn’t even know to look for, leaving no angle of your data unturned — the power of working with an AI-powered analyst who never sleeps.
  9. Ready for ‘anyone’ to explore — Get presentation-ready packs in minutes; statistical results explained in plain english every time, so you’re never left wondering ‘what does this mean’.
  10. Answers when you need them — Intelligence at your fingertips. And no more spreadsheets.

PART 4. The True Value Companies Get From Automated Analytics. In Their Words.

The Value Of Automated Analytics (Real Stories)
Product Feature 1: Automated insights & analytics

Pinpoints problems, raising red flags. Gives ability to resolve issues and fix before it’s too late.

Valuable to teams and leaders working across operational and finance functions where correlations across datasets are tricky to see.

Product Feature 2: Automated reporting & commentary

Better flow of information & intelligence across teams.

Reduces cost of BI teams.

Product Feature 3: Automated root cause analysis

Instant insights closes Q&A loops with senior stakeholders immediately.

Enables agility to respond in real-time.

PART 5. Best Automated Analytics Tools 2021

You will only find one analytics tool in this category that doesn’t require months of training and developing advanced skills to be able to use: this tool is Hyper Anna. Hyper Anna connects to your source systems in one click, automatically understands the specificities of your data and proactively looks for relevant insights. Compare the top business intelligence tools Tableau and Power BI here, and see why Hyper Anna stands out.

PART 6. Why Do I Need Automated Analytics, I’ve Already Got Tableau, Power BI?

Building dashboards sounds great in theory. But terrible if you want to rapidly iterate. Here are the facts.

Traditional BI tools are ineffective. People feel overwhelmed working with data and using legacy BI tools.

So even with 100s (Or 1000s) of dashboards in your organisation, getting from data to decisions is still a huge pain:

  1. Business users want to make data-driven decisions on the fly but can’t perform the analysis on their own.
  2. Dashboards are time-consuming, expensive to build and don’t cater for follow-up or ad-hoc questions. Results in many dashboards built for a single-use and never used again.
  3. Data experts want advanced analytical work but spend most of their time with ad-hoc daily requests

Traditional BI (even with better UI & search) only solves for half of the challenges faced by business users in finding & creating insights by themselves.

Business users face two key struggles when needing to discover insights:

  1. Lack of technical skills (SQL, writing formulas)
  2. Lack of analytical thinking (knowing what questions to ask, how to break down questions to a line of enquiries, how to structure analysis)
‘Search-as-an-Interface’ is not the answer.

In recent years, better UI/UX and Search-as-an-Interface has helped reduce the barrier of technical skills. However, these improvements don’t solve for the lack of analytical thinking that business users require.

In fact, Search create more noise (i.e. what should I ask? What’s important to know? What’s in the data?) rather than signals — powerful insights that move the dial.

Automated Analytics Leader — Hyper Anna
Giving each individual a spreadsheet or a visual analytics tool, and pointing them to a set of databases, no longer does the job — if it ever did.” - Tom Davenport on The Shift To Collaborative Analytics

Tools like Tableau are superb because with a trained hand (this is key), the user can explore data quickly, speedily and find a nugget of information — like Indiana Jones hunting for that killer artefact. But the end user of the dashboard created is driven by assumptions made by the dashboard designer. It adds a layer of complexity to the user to also be an amateur archaeologist to find what they need specifically at that point in time.

Ravi Mistry on Dashboards - Rarely What People Need

CONCLUSION: Looking to read a bit more?

Our 100 page book is the go to automated analytics guide. Bite size, data led intelligence for busy people.


The Ultimate Guide To Automated Analytics (2021)

Bottomline — 100 pages of expert advice. 5 years of research. Real strategies and tactics for application. Absolutely free.

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