2. INTRODUCTION
With 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.
3. 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
5. 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.
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6. 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 Smith
TechStorm
8. 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
10. 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.
10
12. 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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14. 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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15. 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 Nanji
ImproveCX
In 2017, companies will need to:
• React to new and changing trends fast,
• Understand customer behaviours,
• Create data-driven products & services.
17. 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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18. 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 Patel
ImproveCX
20. 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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22. 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 Smith
Tech Storm
24. 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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25. 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 Hollander
ImproveCX
27. 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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28. 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.
