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Leveraging Big Data & Analytics in the Public Sector March 29 30, 2016 Ottawa, Ontario YOUR FACULTY GET ADVICE FROM INDUSTRY EXPERTS Bruce Angevin, Director Operational Excellence and IT Strategy,
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How to fill out leveraging big data analytics

How to Fill Out Leveraging Big Data Analytics:
01
Identify business objectives: Before beginning to leverage big data analytics, it is crucial to identify the specific business objectives that you want to achieve. This could include improving customer experience, increasing operational efficiency, or optimizing marketing campaigns.
02
Gather data: The next step is to gather the necessary data to support your objectives. This may involve collecting data from various sources such as customer databases, social media platforms, sensors, or third-party sources. It is important to ensure that the data collected is relevant, accurate, and of high quality.
03
Clean and prepare the data: Once you have gathered the data, it is essential to clean and prepare it for analysis. This involves removing any duplicate or erroneous data, handling missing values, and transforming the data into a usable format. Data cleaning and preparation are crucial for ensuring accurate and reliable insights from the analytics process.
04
Choose the right analytics tools: There are numerous analytics tools available in the market, ranging from open-source options to advanced commercial platforms. Selecting the right tool depends on your specific requirements, available resources, and budget. It is important to consider the tool's capabilities for handling big data, scalability, ease of use, and compatibility with your existing systems.
05
Perform exploratory analysis: Once the data is prepared and the analytics tool is set up, you can start exploring the data through various analytical techniques. This involves identifying patterns, trends, and relationships within the data to gain initial insights. Exploratory analysis helps in understanding the data better and identifying potential areas for further investigation.
06
Apply advanced analytics techniques: Take advantage of advanced analytics techniques such as predictive modeling, machine learning, or natural language processing to extract meaningful insights from the data. These techniques can help in identifying patterns, making predictions, detecting anomalies, or automating decision-making processes.
07
Interpret and communicate the results: After performing the analysis, it is important to interpret the results in the context of your business objectives. This involves extracting actionable insights from the analytics findings and considering any limitations or potential risks associated with the results. Communicate the insights effectively to relevant stakeholders, using visualizations or reports that are easy to understand.
Who Needs Leveraging Big Data Analytics:
01
Businesses in competitive industries: Leveraging big data analytics can provide businesses in competitive industries with a competitive advantage. By analyzing large volumes of data, businesses can gain insights into market trends, customer behavior, and competitor strategies, allowing them to make data-driven decisions and outperform their competition.
02
Enterprises with large and complex datasets: Big data analytics is particularly beneficial for enterprises dealing with large and complex datasets. Traditional analytics tools may struggle to handle the volume, variety, and velocity of big data. Leveraging big data analytics allows these enterprises to extract valuable insights that may otherwise remain hidden in their data.
03
Industries with customer-centric focus: Industries such as retail, e-commerce, banking, and telecommunications, which have a strong customer-centric focus, greatly benefit from leveraging big data analytics. By analyzing customer data, these industries can gain a deep understanding of their customers' preferences, behavior, and needs, enabling them to personalize their offerings, improve customer experience, and drive customer loyalty.
04
Organizations aiming for data-driven decision-making: Leveraging big data analytics is crucial for organizations that strive to make data-driven decisions. By analyzing data in real-time, organizations can make informed decisions, optimize processes, and identify opportunities or risks. This helps in enhancing operational efficiency, reducing costs, and achieving business goals.
05
Government agencies and public sector organizations: Governments and public sector organizations can harness the power of big data analytics to drive evidence-based policymaking, improve public services, and enhance public safety. Big data analytics can assist in identifying patterns in crime data, optimizing traffic management, predicting disease outbreaks, or analyzing social media sentiment to understand public opinion.
In summary, leveraging big data analytics requires identifying business objectives, gathering and preparing data, choosing the right analytics tools, performing exploratory analysis, applying advanced analytics techniques, and interpreting and communicating the results. Those who can benefit from leveraging big data analytics include businesses in competitive industries, enterprises with large and complex datasets, customer-centric industries, organizations aiming for data-driven decision-making, and government agencies or public sector organizations.
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