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INTRODUCTIONWith the help of our partners ImproveCX and TechStorm we elected 10 trends that will shape the Business Intelligence landscape in 2017.

Improve CX specialised in being close to consumers, understanding new technologies and markets in order to produce differenciated Customer Experiences.

TechStorm is an IT Services organisation focused on the Digital world, transforming business objectives into cutting-edge, highly functional solutions.

01 Artificial Intelligence

02 Mobile BI

03 Modern BI

04 Data Quality

05 Internet of Things

06 Natural Language

07 Data Visualisation

08 Self-service preparation

09 Big Data

10 Hybrid Solutions

01

ARTIFICIAL INTELLIGENCE

ARTIFICIAL INTELLIGENCE

Artificial Intelligence includes tech-nologies such as deep learning, neural networks and natural language processing.

Many of these are being applied to BI to improve decision-making.

Some examples include predictive data mining, machine learning, sim-ulation, looking for trends, anomaly detection and even autonomous decisions.

But how does it impact our daily work?

BI users will experience Artificial Intel-ligence impact in three main ways:- Through advanced analytics,- AI-powered and autonomous busi-ness processes, - AI conversational interfaces.

Imagine a scenario where a chat bot warns you about what is going to happen:

- You are going to miss your forecast;

and advises you on the best decision to correct a problem:

- You should launch your campaign this week to meet your goal.

This is the next step for data-driven decisions.

Intelligent agents that provide you with business advice won’t go mainstream next year. However, we are definitely expecting to see interesting advances on this field during 2017.

05

No longer the stuff of Sci-fi writers, AI is here and will change how we use data in an

increasingly cognitive way.

So, think Push instead of Pull, think the ability to have the Data analysed by your own

personal Data Scientist, real-time.

“

Tony SmithTechStorm

02

MOBILE BI

MOBILE BI

A couple of years ago BI products with mobile versions started to emerge. The problem was that Mobile BI was seen as a way to get figures when you are not at the office. It ended up being the same static reports and old dashboards only adapted to fit a smaller screen.

While most BI vendors are stuck on that approach, others are developing different ways to interact with data, such as natural language interfaces. These are more suitable for mobile, as they mimic the kind of behavior users have with consumer apps.

Just like with Google Go and Siri, us-ers can speak or type questions and get their answer on the spot.

“Nomad” workers, like sales reps, could profit from having an easier

and more interactive ways to access information.

In 2017, BI products’ UX for mobile will be improved. It’s going to become more interactive, less limitative and more close to the kind of experience users already have with consumer apps.

08

Right Here, Right now: I expect to be able to view all the data I want on any device, anywhere, any-time. Not just when I get back to the homestead.

Tony Smith

Tech Storm

03

MODERN BI

MODERN BI

According to Gartner, BI has definitel-ly shifted from a “IT-led reporting to business-led self-service analytics”.

This is a consequence of companies not buying, or at least buying less, IT-centric tools and traditional vendors not betting on innovation.

Gartner’s 2016 Magic Quadrant for BI and Analytics reflected such change, and pointed the birth of what they call Modern BI.

In Gartner’s words Modern BI is a “self-contained architecture that enables nontechnical users to autonomously execute full-spectrum analytic workflows from data access,

ingestion and preparation to interactive analysis and the collaborative sharing of insights.”

This means IT teams will assume more of a facilitator role, leaving analytics authorship and data preparation for business users.

Gartner also states that a Modern BI should have these three features: - Natural Language Query and Search; - Self-Service Data Ingestion; - Big Data Source Connectivity.

In 2017, we will see BI vendors trying to add those type of capabilities, in order to stay relevant and ahead of innovation.

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04

DATA QUALITY

DATA QUALITY

It’s important to have easier ways to analyse data, but it’s equally relevant to have accurate data.

Companies understand that great visualizations are nothing without high quality data, otherwise you would be condemned to make wrong decisions.

In 2017 we will see a shift on funding. Organizations are ready to invest on data quality management. Compa-nies will start to leverage technologies to monitor their data.

BI tools with data quality manage-ment capabilities should support:- Data Profiling, - Data Quality, - Data Integration, -Data Augmentation.

Also, as business users are expected to prepare data for analysis to gain speed, IT will need to act as vigilantes to ensure data quality and safety.

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05

INTERNET OF THINGS

IoT

With IoT we can’t avoid the feeling that we are on the edge of achieving a breakthrough but something is holding us back.

The number and variety of IoT devices keeps growing: wearables, drones, autonomous cars and so on.

According to Gartner there will be six billion connected things requesting data support by 2018.

As the volume of IoT data grows, so does the potential for insights.

The “2016 The Internet of Things and Business Intelligence Market Study” by Dresner Advisory Services, published in October, states that for organizations, IoT is a core justification for investing in and

implementing big data analytics and architectures.

Even sales are ranking IoT highly, indicating that companies are attempting to launch business models and drive revenue from IoT.

This is an important change on how companies perceive IoT, from something distant to something that can boost their businesses.

For BI tools, this means they must be able to deal with even greater amounts of data in real time and without compromising security.

Users expect to access data no matter what size or where it comes from.

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IoT has been accelerated by the internet, mobile/sensor devices, cloud services and applications, means gathering of this data, mining for insights and then taking action has become imperative.

“

Sam NanjiImproveCX

In 2017, companies will need to:• React to new and changing trends fast,• Understand customer behaviours,• Create data-driven products & services.

06

NATURAL LANGUAGE

NATURAL LANGUAGE

As screens are getting smaller and smaller we need to come up with different ways to interact with data.

Natural Language and bots are the next step when it comes to Business Intelligence interfaces.

To extract insights from business data users will speak or type queries in a search box or in a chat.

The software will need to understand the query, analyse the data and present a chart automatically.

It’s a completely different approach

from what we have seen so far.

This means BI is shifting from a model where people adapt to computers to one where the computer “hears” and adapts to a person.

In 2016, we saw the rise of the first four players on Natural Language BI: Wizdee, Power BI, Thoughtspot and Google.

With Gartner promoting Natural Language Search as a must-have in a Modern BI tool, we’ll see more players adding this type of capabilities.

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Voice, Gesture, AR, and VR will drive user experiences as more users are talking and swiping

than mousing and typing.

Cognitive and behavioral models and integrated practices create smart interfaces that

adapt presentations to context and anticipate our next desire.

“

Raj PatelImproveCX

07

DATA VISUALISATION

DATA VISUALISATION

Gone are those days when users would settle for static reports and charts.

Users want to interact with their data, charts and dashboards, preferably without IT help.

The goal of Data Discovery is putting the power of data analysis into the hands of business users. For that to happen BI tools need to continue their path towards simplification.

Conversational/voice interfaces seem to be the newest and easiest way to perform analytics. In 2017 the num-ber of vendors offering this kind of solution should increase significantly.

This requires visualisations to be automatically generated, instead of having users to drag and drop metrics to create a chart.

It’s a significant change, specially because all the major BI vendors are still limited to the second option.

Plus, data visualization and interactive data analysis now have to deal with more complex data sources.

BI vendors will need to remain on their toes.

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08

SELF-PREPARATION

SELF-PREPARATION

In 2016 Gartner included self-service data preparation as requirement for a BI tool to be consider modern. As result, self-service data preparation tools exploded in popularity.

The number of options for end users to “prepare” all forms of data are growing.

Business users want to be able to reduce the time and complexity of preparing data for analysis.

It means spending less time on

upfront model, as users can access un-modelled data to adjust and blend it with self-preparation data capabili-ties incorporated in the platform.

Nevertheless, it’s important for IT to continuosly oversee data quality and governance.

Stryke the balance can be hard, but well worth it.

We’ve seen a host of innovation in this space and it will only grow during 2017.

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Data is no longer owned by IT. Business users demand access to data without having to make laborious requests to get what they need. Smart organisations will fulfil these demands.

Tony SmithTech Storm

09

BIG DATA

BIG DATA

We continue generating larger and larger volumes of data. With the number of Internet-connected devices on the edge of exploding, big may no longer be the best word to define the amount of data we create.

Next year, the big data trend will evolve in two fronts.

First, IoT, cloud and big data will come together. This started in 2016 with companies such as Google, Amazon and Microsoft presenting

IoT products which allow the data to move seamlessly to their cloud based analytics engines.

On the other hand, as the data volume grows so do the costs and security issues.

To make up for those costs, organizations will attempt to mone-tize their data, which will lead to the breakout of data-as-a-service (DaaS).

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Analytics will be driving our decisions in a big data driven world and will improve in both ubiquity and

user friendliness for applications from the con-sumer to the enterprise.

AI will play an increasing role in solving complex problems and our choices will be served

to us by machines.

“

Ryan HollanderImproveCX

10

HYBRID SOLUTIONS

HYBRID SOLUTIONS

This trend is all about BI deployment. The ubiquity of the cloud is nothing new. The number of cloud-based tools available on the market is growing fast. As more and more enterprise software and data sources move to the cloud so will BI.

This is driven by users’ demand for faster answers anywhere. The increasing volume of data (coming from IT for instance) and cheaper cloud solutions are also reasons to

abandon on premises models.

However, while business users tend to easily accept cloud deployment, IT teams have serious security concerns. IT tends to prefer on premises deployment.

BI solutions will evolve to satisfy both needs. Hybrid solutions which include cloud and on premises deployment will end up being the new norm.

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TRY THE FUTURE NOW

TRY NOW

You can have a taste of BI’s future with Wizdee Free Trial.

Explore data just by speaking or typing queries in a search box using everyday language and it automatically presents the best visualization.

You can use Wizdee for free for 15 days. Connect it with samples data, your Salesforce or Excel. No credit card required, it's just plug and play.

wizdee.comimprovecx.com techstorm.ie