4. Prescriptive analytics :

• Prescriptive analysis recommends actions you can take to affect a desired outcome. Beyond just showing future trends, prescriptive analytics suggests different courses of action to best take advantage of the predicted future scenario.
• For instance, imagine a business scenario where predictive analytics tells you which customers are most likely to churn in the next quarter. Prescriptive analytics suggests specific retention strategies tailored to each at-risk customer segment, such as special discount offers, loyalty programs, or personalized communication campaigns.
• The essential Infrastructure technologies required for Advanced Data Analytics are- Internet of Things, Storage, Computing, Visualization, Security. In this Advanced Data Analytics, Artificial Intelligence And Machine Learning Technology is used.

1. Definition and Purpose :

• Big data consulting services are advisory activities aimed at providing professional support to businesses to turn their data into a tangible value driver.
• ScienceSoft offers full-scope big data consulting at any stage of a big data initiative

2. Big Data Overview: :

• Big data is vast and complicated data that typical data processing systems cannot collect, manage, or handle.
• Big data can be structured, unstructured, or semi-structured.
• The practice of evaluating, cleansing, transforming, and modeling this data to uncover usable information and meaningful conclusions is known as big data analytics.

3. Benefits of Big Data Analytics :

• Helps businesses find new business opportunities.
• Accelerates the decision-making process.
• Alerts the enterprise by identifying underlying danger and problems.

4. Role of Big Data Analysts :

• Scrutinize massive enterprise data sets to uncover hidden patterns and correlations.
• Help businesses with meaningful insights.

5. Role of Big Data Analysts :

• Scrutinize massive enterprise data sets to uncover hidden patterns and correlations.
• Help businesses with meaningful insights.

6. Collaboration with Big Data Consulting Firms :

• Creating an in-house Big Data and Data Engineering department can be expensive.
• Organizations collaborate with big data analytics consulting firms to harness the potential of big data without enormous initial investment.

7. Benefits of Big Data Consulting Services :

• Help organizations leverage advanced data analytics to process datasets and derive business insights.
• Suggest the most effective strategy to leverage this data.

9. Partnering with Big Data Consulting Firms :

• Get customized recommendations based on the organization’s current enterprise setup and expected outcomes.
• Focus on core jobs instead of worrying about big data solution implementation.
• Adhere to compliance and regulatory guidelines without jeopardizing big data projects.
• Apply industry best practices to get faster and better results.

8. A2DGC's Big Data Service Offering: :

• Big Data Collection
• Big Data Processing
• Big Data Analysis
• Big Data Innovation
• Big Data Planning

1. Definition and Goal :

• Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively.
• The goal is to optimize the use of data within policy and regulation bounds to maximize organizational benefit.

2. Importance :

• A robust data management strategy is crucial as organizations increasingly rely on intangible assets to create value.

3. Scope of Data Management: :

Key tasks include :
• Creating, accessing, and updating data across a diverse data tier.
• Storing data across multiple clouds and on-premises.
• Providing high availability and disaster recovery.
• Using data in various apps, analytics, and algorithms.
• Ensuring data privacy and security.
• Archiving and destroying data according to retention schedules and compliance requirements.

4. Components of a Data Management Strategy :

• Addresses the activity of users and administrators.
• Considers the capabilities of data management technologies.
• Meets regulatory requirements.
• Aims to obtain value from organizational data.

5. Fundamental Data Management Disciplines :

• Data Modeling : Diagrams the relationships between data elements and how data flows through systems.
• Data Integration : Combines data from different sources for operational and analytical uses.
• Data Governance : Sets policies and procedures to ensure data consistency throughout the organization.
• Data Quality Management : Aims to fix data errors and inconsistencies.
• Master Data Management (MDM) : Creates a common set of reference data on things like customers and products.

1. Definition and Role :

• Strategy consultants provide in-depth industry knowledge and impartial advice for major decisions, aiming to achieve the best outcomes for organizations.
• It is a subset of management consulting, often advising a company's top management.

2. Scope of Work :

• Strategy consultants collaborate with organizations from both the public and private sectors across various industries.

3. Example Scenario :

• Evaluate if it's a wise decision.
• Determine which plant to close.
• Calculate potential savings and losses.
• Restructure the supply chain to manage the loss of production.

4. How Strategy Consulting Works :

• A strategy consultant starts by analyzing the client's goals and objectives.
• They assess if current methods align with desired outcomes.
• Based on their analysis, they offer strategic recommendations to improve results.

5. Areas of Advice :

• Budgeting Advice: Tips on reducing expenses and increasing revenue
• Production Tactics: Advice on improving the efficiency of product production.
• Opportunity Management: Identifying potential income sources or new product lines.

6. Implementation Assistance :

• Consultants may assist with the implementation of their recommendations.

1. Definition :

• Predictive and prescriptive analytics inform business strategies based on collected data.
• Predictive analytics forecasts potential future outcomes.
• Prescriptive analytics provides specific recommendations for optimal decisions.

2. Combined Use :

• Both analytics types should be used together to shift business strategy and create the best possible outcomes.

3. Expert Insight :

• Mick Hollison, president of Cloudera: “Predictive by itself is not enough to keep up with the increasingly competitive landscape. Prescriptive analytics provides intelligent recommendations for the optimal next steps to drive desired outcomes or accelerate results.

4. Predictive Analytics :

• An advanced analytics category that forecasts potential outcomes or decision repercussions.
• Utilizes mined data, historical figures, and statistics to peer into future scenarios.
• Previously accessible mainly to enterprise-level businesses, now available to smaller companies due to SaaS and CRM analytics.
• Involves filtering out superfluous or misleading data to avoid distorted insights.
• Looks at future scenarios using advanced mathematical algorithms, AI, and machine learning.
• Can show multiple options and outcomes, adjusting predictions and suggestions as more data comes in.
• Immanuel Lee, data-driven digital strategist: “Prescriptive analytics can help companies alter the future. Both types are necessary to improve decision-making and business outcomes.”

1. Definition :

• Data Analytics Outsourcing involves a company trusting an analytics service provider with its data to receive actionable insights.
• The service provider handles everything from infrastructure set-up and maintenance to data management and analysis.

2. Types of Analytics and Insights Providers :

Analytics and KPO Players :
• Proficient with data and AI capabilities.
• Have sufficient domain expertise.

Insights Vendors :
• Companies like Kantar and Nielsen.
• Specialize in domain understanding.

System Integrators (IT/BPO) :
• Companies like Accenture and Capgemini.
• Offer a balance between domain expertise and data capabilities.

3. Utilization of the Standard :

• Governmental agencies, scheme owners, and others may use ISO/IEC 17024:2012 as a criteria document.
• It can be used for accreditation, peer evaluation, or recognition purposes.

4. Benefits of Data Analytics Outsourcing :

• Industry Expertise: Access to specialized knowledge and skills.
• Talent Acquisition: Ability to leverage external talent.
• Business Flexibility: Adaptable to changing business needs.
• Regulation Compliance: Ensures adherence to industry regulations.
• Customer Focus: Allows the company to concentrate on core business activities.
• Saving Costs: Reduces expenses related to analytics infrastructure and talent.
• Benefits of Data Analytics Outsourcing
1. Project Based: Specific projects handled by the service provider.
2. Analytics Team Extension: Extending the company's analytics team with external experts.