SGS Technologie

Data is everywhere. Each incident, conversation or transaction can be regarded as data. It is just virtually anything that happens in the world.  Big Data refers to the process of collecting such data and storing it in a single archive or infrastructure.  It can be large datasets or even strategies and technologies that are used to handle such large data sets. Yet such massive amounts of data can be of value, only if they are analyzed and if insights are generated from them. This is the general meaning of big data analytics.

Big Data Analytics also examines large amounts of data to uncover hidden patterns, correlations and other insights. Organizations collect data that they have gathered from customers, businesses and practical experience. Data is then processed after gathering and is categorized as per the requirement and analysis is done to study purchase patterns and other information.

Big data analytics then helps organizations harness their data and use it to identify new opportunities.

Types of Big Data Analytics:

Three forms of big data analytics are commonly followed. These are:

Descriptive Analytics:  A simple explanation about this type of analytics will be that the process collects or mines different sources of data to narrate “What has happened”? It is an analysis of various events, transactions or sharing of information in the past; perhaps even for a particular period of time. This can be useful to study moods or trends for a particular period of time that can be a year or even day before. Strategies and tools of descriptive analytics are useful as this information can be used to understand how business or even the economy may be influenced in the future.

Predictive Analytics: As stated in the term, predictive analytics is predicting what will happen in the future. This analysis gives an idea about what would happen in the future based on a business’ past and the strategies it is follows. Hence, prescriptive analytics can be utilized to examine if a business, department or even an individual professional is currently following the right approach or now.  In fact credit scores are calculated using predictive analysis. These scores are used by financial services to determine the probability of customers making future credit payments on time. Businesses can also use predictive analytical tools and strategies to understand how sales might close at the end of the year, predicting what items customers will purchase together, or forecasting inventory levels based upon a myriad of variables.

Prescriptive Analytics: This provides suggestions or prescriptions that a business can take in instances that have been analyzed; in the past or future. For example, analyzing the trends and transactions of the past would have observed certain flaws in an approach that a business is presently following. Prescriptive analytics provide advice on what steps need to be taken to avoid poor decisions and probability of losses in the future. It helps companies make decisions that reflect customers’ needs and changing trends.

Advantages of Big Data Analytics:

Cost and time reduction. Big data technologies and cloud-based analytics assist in saving costs by a very large margin while storing tons of data. For example, a government department or agency may have to store millions of files regarding people in the area, businesses, financial plans, and more. Storage of such data in paper form is outdated.  Computer systems on the other hand may require large amounts of investment on multiple systems and storage spaces. The costs in storing data through such methods can be very high and also pose intense difficulties in accurately retrieving the required data. A much better alternative will be to use big data technologies such as Hadoop and cloud-based analytics. A single virtual file stores all the data a business or department will require. Only a single-time-investment along with enabling easy fetching of required information at anytime is required for this.

Access to Accurate Information: The mining, collection and analysis of big data are done with the assistance of technological tools as well as professional strategies. The information thus stored and accessed will be 100% accurate. It should be observed that inputs for big data are taken from multiple sources that are spread across varied locations and time zones.  Moreover these inputs are collected by big data tools and business intelligence strategies. The mining of information will in no way be affected by human preferences. Hence big data gives access to accurate information on the moods of the audience, indications of growing trends as well as genuine user feedback. These facts can be analyzed and used to make corrections in current business strategies or be used as the base to launch new products/services.

Faster, better decision making. Big Data Analytics can help businesses make swift and productive decisions. This statement can be explained by considering the life-cycle of a business campaign or perhaps even corporate and government initiatives. Each time a new product, service or campaign is planned, a business may need to consider the current trends, mood of the target audience and government policies among other things. Research on these factors, analyzing them and finally creating strategies could take a lot of time. Usage of Big Data technologies enables the collection and storage of all this information in one single archive. Big Data Analytics facilitate quicker comprehension and summarizing value inputs from this, enabling better business decisions within a short period time.

Unique data analytical strategies can be implemented for different businesses or organizations. Contact SGS Technologie for a discussion on the best solution for your company.

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Why Big Data Analytics for your business?

 158

Data is everywhere. Each incident, conversation or transaction can be regarded as data. It is just virtually anything that happens in the world.  Big Data refers to the process of collecting such data and storing it in a single archive or infrastructure.  It can be large datasets or even strategies and technologies that are used to handle such large data sets. Yet such massive amounts of data can be of value, only if they are analyzed and if insights are generated from them. This is the general meaning of big data analytics.

Big Data Analytics also examines large amounts of data to uncover hidden patterns, correlations and other insights. Organizations collect data that they have gathered from customers, businesses and practical experience. Data is then processed after gathering and is categorized as per the requirement and analysis is done to study purchase patterns and other information.

Big data analytics then helps organizations harness their data and use it to identify new opportunities.

Types of Big Data Analytics:

Three forms of big data analytics are commonly followed. These are:

Descriptive Analytics:  A simple explanation about this type of analytics will be that the process collects or mines different sources of data to narrate “What has happened”? It is an analysis of various events, transactions or sharing of information in the past; perhaps even for a particular period of time. This can be useful to study moods or trends for a particular period of time that can be a year or even day before. Strategies and tools of descriptive analytics are useful as this information can be used to understand how business or even the economy may be influenced in the future.

Predictive Analytics: As stated in the term, predictive analytics is predicting what will happen in the future. This analysis gives an idea about what would happen in the future based on a business’ past and the strategies it is follows. Hence, prescriptive analytics can be utilized to examine if a business, department or even an individual professional is currently following the right approach or now.  In fact credit scores are calculated using predictive analysis. These scores are used by financial services to determine the probability of customers making future credit payments on time. Businesses can also use predictive analytical tools and strategies to understand how sales might close at the end of the year, predicting what items customers will purchase together, or forecasting inventory levels based upon a myriad of variables.

Prescriptive Analytics: This provides suggestions or prescriptions that a business can take in instances that have been analyzed; in the past or future. For example, analyzing the trends and transactions of the past would have observed certain flaws in an approach that a business is presently following. Prescriptive analytics provide advice on what steps need to be taken to avoid poor decisions and probability of losses in the future. It helps companies make decisions that reflect customers’ needs and changing trends.

Advantages of Big Data Analytics:

Cost and time reduction. Big data technologies and cloud-based analytics assist in saving costs by a very large margin while storing tons of data. For example, a government department or agency may have to store millions of files regarding people in the area, businesses, financial plans, and more. Storage of such data in paper form is outdated.  Computer systems on the other hand may require large amounts of investment on multiple systems and storage spaces. The costs in storing data through such methods can be very high and also pose intense difficulties in accurately retrieving the required data. A much better alternative will be to use big data technologies such as Hadoop and cloud-based analytics. A single virtual file stores all the data a business or department will require. Only a single-time-investment along with enabling easy fetching of required information at anytime is required for this.

Access to Accurate Information: The mining, collection and analysis of big data are done with the assistance of technological tools as well as professional strategies. The information thus stored and accessed will be 100% accurate. It should be observed that inputs for big data are taken from multiple sources that are spread across varied locations and time zones.  Moreover these inputs are collected by big data tools and business intelligence strategies. The mining of information will in no way be affected by human preferences. Hence big data gives access to accurate information on the moods of the audience, indications of growing trends as well as genuine user feedback. These facts can be analyzed and used to make corrections in current business strategies or be used as the base to launch new products/services.

Faster, better decision making. Big Data Analytics can help businesses make swift and productive decisions. This statement can be explained by considering the life-cycle of a business campaign or perhaps even corporate and government initiatives. Each time a new product, service or campaign is planned, a business may need to consider the current trends, mood of the target audience and government policies among other things. Research on these factors, analyzing them and finally creating strategies could take a lot of time. Usage of Big Data technologies enables the collection and storage of all this information in one single archive. Big Data Analytics facilitate quicker comprehension and summarizing value inputs from this, enabling better business decisions within a short period time.

Unique data analytical strategies can be implemented for different businesses or organizations. Contact SGS Technologie for a discussion on the best solution for your company.

Category : Big Data

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