How Business Intelligence is Changing with the Use of Real-time Analytics - PowerPoint PPT Presentation

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How Business Intelligence is Changing with the Use of Real-time Analytics

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The process of using real-time analytics to deliver information on business operations as and when they occur is Real-time Business Intelligence. Real-time analytics is gradually gaining importance in this rapidly advancing digital age. Several prominent companies are developing business intelligence platforms to fuel the growth of the global analytics market. Let us discuss how streaming analytics is redefining business intelligence. – PowerPoint PPT presentation

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Date added: 30 January 2019
Slides: 11
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Title: How Business Intelligence is Changing with the Use of Real-time Analytics


1
How Business Intelligence is Changing with the
Use of Real-time Analytics
2
Data and analytics
  • Data is growing faster than ever before and by
    the year 2020, about 1.7 megabytes of new
    information will be created every second for
    every human being on the planet.
  • We are seeing a massive growth in video and photo
    data, where every minute up to 300 hours of video
    are uploaded to YouTube alone.
  • Real-time and streaming analytics is gradually
    gaining importance in this rapidly advancing
    digital age.
  • Several prominent companies are developing
    business intelligence platforms to fuel the
    growth of the global analytics market.
  • According to a report, the market for analytics
    will possibly reach USD 9.50 billion by 2023 at a
    CAGR of 20.50 during the period.

3
What is historical data analysis?
  • Historical Data Analysis is primarily focused on
    analysing data of the past.
  • For historical data analysis, analysts attempt to
    analyse data by exporting relevant data from a
    past day, month, quarter or any earlier period of
    time.
  • They will then perform one or more of three
    different types of analyses.
  • - Descriptive Analytics
  • - Predictive Analytics
  • - Prescriptive Analytics

4
  • Descriptive Analytics
  • Descriptive analysis creates a concise story from
    a segment of historical data. The story will
    ideally have an overall theme.
  • Descriptive analytics enables analysts to
    understand past events and also allows them to
    build predictive and prescriptive analytical
    models.
  • Predictive Analytics
  • Predictive Analytics analyzes trends in data to
    predict future events and occurrences.
  • Analysts showcase likely scenarios with the help
    of Data Mining, Statistics and Machine Learning.
  • Prescriptive Analytics
  • Prescriptive Analytics seeks to inform data
    analysts about what to do.
  • In this process analyst analyses the data and
    prescribes real-world decisions that businesses
    can adopt.

5
Real-time or streaming analytics
  • Real-time analytics analyses and perform actions
    on data as it becomes available i.e. real-time
    data through continuous queries.
  • Analysts are able to make critical operational
    decisions and apply them to business processes or
    transactions in real time and on an on-going
    basis
  • Stream Processing allows analysts to apply
    pre-existing predictive or prescriptive models
  • Historical data tells us what has happened in the
    past while real-time analytics tells us what is
    happening in the present.
  • Streaming Analytics enables businesses to receive
    alerts based on certain, predefined parameters,
    thereby automating the data analysis processes.
  • Real-time analytics allows marketers and analysts
    to visualise and monitor dashboards in real time
    on constantly-changing transactional data sets
    such as the hourly sales of a set of regional
    grocery stores

6
Advantages of real-time analytics
  • Data Visualization
  • Streaming data can be visualized in such a way
    that updates are received in real time to show
    what is occurring at that moment.
  • It makes easier to visualize the data in
    real-time so that quick actions can be taken to
    improve the business performance.
  • Business Insights
  • Real-time analytics can effectively track the
    occurrence of critical business events.
  • If there is any sort of unusual activity that is
    reported, alerts can be triggered to inform the
    management, so that suitable action can be taken.
  • Increased competitiveness
  • By tapping the potential of real-time or
    streaming analytics, businesses can analyze
    trends and set benchmarks much more quickly.
  • This will allow marketers and analysts to use
    this data to stay ahead of competitors who may
    still be using the slower process of batch
    analysis.

7
Streaming big data and BI
  • The process of using real-time analytics to
    deliver information on business operations as and
    when they occur is Real-time Business
    Intelligence.
  • The term real-time signifies minimal or
    negligible latency.
  • In this process, information becomes accessible
    anywhere between milliseconds to five seconds
    after it occurs.

8
How does real-time analysis bring value to
businesses?
  • Minimizing preventable losses. Streaming
    analytics prevents or minimizes any damage caused
    by events such as security breaches,
    manufacturing defects, customer churn etc.
  • Analyzing routine business operations. Operations
    such as IT systems, manufacturing closed-loop
    control systems, and financial transactions such
    as authentications and validations can be
    monitored in real time.
  • Finding missed opportunities. The streaming and
    analysis of Big Data can help businesses learn
    from customers behavioral trends as well as
    immediately recommend, upsell, and cross-sell to
    them based on what the information presents.
  • Create new opportunities. The existence of
    streaming data technology has resulted in the
    invention of new business models, product
    innovations, and revenue streams.

9
Use cases of real-time streaming analysis
  • BuzzFeed uses real-time streaming analytics to
    analyze articles views and how they are shared to
    better understand how website visitors are
    interacting with more than 400 million news items
    that are published every month. BuzzFeed can then
    utilize these metrics to effectively devise ways
    to increase website engagement.
  • Marketing departments can effectively draw upon
    the potential of real-time analytics to conduct
    A/B and multivariate tests, keep track of digital
    campaigns in real-time, access results quickly,
    in an effort to offer personalized website
    experiences to users and audiences.
  • Cyber security, weather forecasts, healthcare and
    manufacturing can use real-time data analytics to
    improve the performance.

10
Final words
  • The prominence of real-time and streaming
    analytics is increasing every year.
  • The amount of data being generated by various
    businesses and organizations is steadily
    increasing.
  • In the absence of real-time analytics, it is
    becoming more and more challenging to gain
    meaningful insights from this huge pool of data.

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