denodo datafest 2017: trending topics in bi and data management

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Trending Topics in BI & Data Management London, Denodo DataFest 2017 Timm Grosser, Head of Consulting: BI & Data Management

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Page 1: Denodo DataFest 2017: Trending Topics in BI and Data Management

Trending Topics in BI & Data ManagementLondon, Denodo DataFest 2017

Timm Grosser, Head of Consulting: BI & Data Management

Page 2: Denodo DataFest 2017: Trending Topics in BI and Data Management

© BARC

About the CXP Group

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IT Meta-Trends

32017

Digitalization

Consumerization

Agility

Security & Privacy

Cloud

User Enablement

Artificial Intelligence

Mobile

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2,800 BI practitioners have their say.

The importance of BI and data management trends

42017Source: BARC BI Trend Monitor 2018, n= 2770

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3 Findings

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BI / analytics doesn't make sense

without a solid data foundation(DQ/ MDM the top trend, data governance improved its ranking)

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BI / analytics doesn't make sense without a solid data foundation

Data management is key

How satisfied are you with the following points regarding the way data is currently prepared for analytics?, n:

686, BARC Data Preparation Survey 2017 72017

• Today digitalization leads to higher

expectations and requirements of data,

especially from management and business

departments.

• For years, data management has been

neglected by many organizations.

• The result: most challenges in terms of time

spent from idea to final analysis involve data

management (find, access, validate, blend,

enrich, design).

• Today, companies are starting to understand

that smart data management is necessary to

make the most effective use of data.

• The vision: Rule your data and don‘t get ruled

by your data. New skills, approaches and

technologies needed.

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A culture and organization that enables

companies to work with data is required(Data discovery and self-service are top-ranked,

data integration for business users and collaboration

show strong increases in rankings)

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• High responsiveness and flexibility is required to comply with

dynamic business demands.

• Business users need more autonomy and agility when it comes

to integrating, analyzing and visualizing data

• in BI we often see self-service approaches to

compensate for deficiencies in collaboration or IT.

• for exploration to work with data in a self-service manner

is highly needed.

• Shift of data management competences to business

departments needs an agreed data and tool governance

framework.

• And so: to get the most value from data, we need to align the

knowledge available from business and IT very closely.

A culture and organization that enables companies to work with data is required

Collaboration more valuable than silo self-service approaches

Which benefits do you generate through data preparation? By method of use (n=453) 92017

Collaboration

brings greater

benefits in most

cases

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Digital initiatives drive

real-time analytics and

the use of open / external data(Increase in ranking for real-time analytics and external data)

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Digital initiatives drive real-time analytics and the use of external data

Monetization of data by operationalizing BI

112017

Approaches to operationalizing BI:

1. Embedding classical BI into operational applications

Making reports, dashboards and possibilities for data

analysis and planning available in operational applications

2. Implementing process-oriented BI.

Monitor operational processes to gain real-time information

on quality, time and cost of processes

3. Supporting or automating decisions using models.

Integration of decision models derived from data mining and

machine learning

• Companies are gaining more and more insights from data.

• Much value comes from use cases where companies

operationalize their insights using real-time analytics.

High real-time

relevance

High real-time

relevance

near/ real-time

relevance

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Recommendations

1. Start to rule your data. Data management is key for analytics

2. Enable a culture of working with data – balance between self-service and collaboration is key

3. Do not only explore your data! Operationalize / monetize your insights – there are high benefits in real-time analytics

Action points:

1. Venture into trending topics

2. Train your staff

3. Pay attention to data quality

4. Understand data analysis requirements

5. Review your information architecture and evaluate new technologies

6. Be aware of the challenges of self-service BI

122017

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Your Contact @ BARC

To get full access to the surveys visit us at http://barc-research.com/

@timmgrosser